Foreword

According to modern portfolio theory, risk andreturn go hand in hand. But risk (whether portfoliorisk, firm risk, security risk, or other) rarely gets thesame amount of attention as return does. Forinstance, the annual return on the S&P 500 Index isa commonly mentioned number in the financialpress. But how often does one see the annual volatil­ity of the S&P 500 mentioned?

Risk management for the asset managementworld encompasses a wide variety of concerns, someof which can be measured and quantified and someof which must be handled subjectively. Investorsand asset managers must be prepared to addressthese risks if they are to achieve optimal investmentperformance. That is, investors and managers mustunderstand the principles and practices behind thedesign, implementation, and interpretation of riskmanagement systems for the asset managementindustry.

The authors in this proceedings come at the issueof risk management from many angles, including abehavioral perspective. They cover the topics of riskmanagement during market crises, fiduciary risks,

Terence E. Burns, CFAVice PresidentEducational Products

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firmwide risks, risk management tools, implement­ing risk management systems, and the role of creditrisk in understanding equity risk. And althoughquantifying risk, through the use of such measures asvalue at risk, can help managers and investors get ahandle on risk, subjective judgment must alwayscome into play to make sure that the measures andsystems used are relevant and accurate.

We are grateful to Bluford H. Putnam at CDCInvestment Management Corporation for serving asmoderator for the conference and for providing theintroduction for this book. We also wish to thank allthe authors for their assistance producing this book:Richard M. Bookstaber, Moore Capital Manage­ment; Stephen Kealhofer, KMV Corporation;Andrew W. Lo, Massachusetts Institute of Technol­ogy's Sloan School of Management; Jacques Longer­staey, Goldman Sachs Asset Management; MichelleMcCarthy, Deutsche Bank; Desmond Mac Intyre,General Motors Investment Management Corpora­tion; Robert M. McLaughlin, Eaton & Van Winkle;Brian D. Singer, CFA, Brinson Partners; and CharlesW. Smithson, CIBC World Markets.

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Introduction to Risk ManagementBluford H. PutnamPresidentCDC Investment Management Corporation

Integrating risk analysis into the investment processand into the core operational processes of managingan asset management company requires a commit­ment to discipline. This integration requires using anumber of building-block concepts about risk man­agement, but these building blocks will only improveinvestment performance and the overall returns ofthe asset management company if they are assembledin a theoretically consistent fashion.

Developing a disciplined approach to risk man­agement involves understanding a broad array ofconcepts. In this proceedings, key themes resonatethat will help in guiding the risk management pro­cess toward one of enhancing investment returns.These building-block themes need to be noted upfront because they appear and reappear as importantelements in each presentation. The authors in thisproceedings take these themes and apply them to anumber of key topics, thereby challenging the riskmanagement world.

Building-Block ConceptsThe distinction between risk management and riskmeasurement must always be in the forefront of one'sthoughts. Many risk management departments havenothing to do with risk management and are focusedsolely on risk measurement. The difference is critical.Risk measurement is part of the fiduciary oversightprocess and does not necessarily directly influenceinvestment decisions. Risk management, by contrast,is tightly linked to the assessment of return potentialin the investment process and directly affects theconstruction of portfolios.

For example, calculating the historical IOO-dayvalue at risk (VAR) for a given portfolio is a riskmeasurement task. Risk management requires eval­uating various estimates of risk, including forward­looking or judgment-based measures, then relatingthe risk estimates to return estimates in a portfoliocontext to allow one to make investment decisions.Government regulators, clients of investment com­panies, as well as the chief investment officers andstockholders of investment companies will want toreview risk measurement information as part of an

Editor's note: The opinions in this introduction are solely those ofthe author and are not necessarily related to any of the opinions ofthe other authors in this proceedings.

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ongoing and important due diligence process. Tobenefit from improved risk-return characteristics,however, risk management must be fully and seam­lessly integrated into the investment process.

The appropriate use of judgment is another keybuilding-block concept. Many investors suffer fromthe delusion of "spurious specificity." Historicalmeasures of risk can be calculated to the tenth deci­mal place or more with impressive accuracy. Assert­ing that these pinpoint measures of risk are in anyway, shape, or fashion good forecasts of future risksis, however, a huge leap of faith. Moreover, having aportfolio with return expectations based on aforward-looking view of the world paired with riskestimates based on a backward-looking view of theworld is a prescription for disaster in terms of evalu­ating risk-return trade-offs at the portfolio level. Theconstruction process is internally inconsistent, eventhough this same historical risk measure may pro­vide useful information in the risk oversight process.

Those professionals assigned exclusively to riskmeasurement tasks are notoriously uncomfortablewith making decisions and integrating judgment intothe risk estimation process. Risk management, oncefully integrated into the investment process, is verymuch about the appropriate use of judgment toimprove on the essentially quantitative estimatesfrom the risk measurement calculations.

The key to using judgment effectively in riskmanagement, and in investment processes in general,is to have a strong appreciation of the assumptionsembodied in specific risk-estimation calculations.When developing theory, assumptions are made tosimplify the analysis. When applying theory to prac­tical cases, the user of any theoretical concept needsto check the simplifying assumptions to make surethat they do not embody hidden risks that are notbeing taken into account.

For example, option-pricing theory, in many ofits most commonly used versions, assumes unlimitedborrowing capacity at the risk-free rate, no taxes,perfect market liquidity with continuous prices andno gaps, constant price volatility, and more. Each ofthose assumptions comes with its own danger sig­nals. As Michele McCarthy discusses, knowing thatmany of these assumptions are embedded in com­mon risk measurements can give one the confidenceto use judgment appropriately in the risk manage­ment process.

1

RiskManagement: Principles and Practices

Although this proceedings is about risk manage­ment, a critical and final building-block concept is tofocus on a consistent measure of returns. In general,returns should be measured as the excess return overthe risk-free rate or, in some cases, the excess returnover a given benchmark. To make these measure­ments properly, one needs to train oneself to think ofevery portfolio in two parts: a benchmark portfolioand an overlay portfolio. Even a market-neutralhedge fund should have a benchmark portfolio, evenif it is only the 90-day T-bill rate. For U'S. equities, thebenchmark is commonly the S&P 500 Index. Theoverlay portfolio is simply the total portfolio with thebenchmark positions subtracted. Thinking in termsof benchmark and overlay portfolios, as well as interms of excess returns, greatly enhances the abilityto consistently integrate risk management into theinvestment process.

Probabilities, Prices, andPreferencesIn modern portfolio theory, risk and return are twosides of the same coin. An investor's financial situa­tion is improved if higher returns can be earned forthe same level of risk or if the same returns can beearned by taking less risk. This view of risk and returnassumes a symmetry of preferences for risk taking thatneeds to be explored further. As Andrew Lo discusses,a complete understanding of the relationship betweenrisk and return requires one to think in terms of prob­abilities, prices, and preferences.

A key lesson for those involved with risk man­agement is that the laws of probabilities applyregardless of how the probabilities are estimated.Confusion sometimes occurs between probabilitiesthat are purely objective in nature and those that aresubjective. An objective probability, such as the one­in-six chance of one side of a fair six-sided die comingup "six," is accurately quantifiable. By contrast, anexample of a subjective probability is someone sayingthe probability of life forms existing somewhere elsein the universe is one in six. Such a probability is moreof a belief than a quantifiable estimate, even ifassigned a specific probability. Once probabilities areassigned, however, they follow the same laws. Thatis, if the probability of Event Y is subjectivelyassigned a probability of 0.7, then the probability ofEvent Y not happening is 0.3; Event Y either occurs,or it does not.

Other laws of how to calculate conditional prob­abilities apply as well, regardless of the objective orsubjective nature of the original probability esti­mates. This point may seem trivial and obvious, butwhen one moves into the world of subjective proba-

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bilities, it is not hard to contrive complex cases inwhich the probabilities are inconsistent with eachother. For example, this inconsistency can happenquite easily when one is casually thinking about theprobabilities of the French franc or the German mark,appreciating against the U.S. dollar. Such subjectiveprobabilities of currency movements may be incon­sistent when looked at from another perspective,such as against the U.K. pound or Japanese yen,indicating an inconsistency in the probabilities of thecross-exchange rates. The lesson is that one must beextremely disciplined in manipulating risk and cor­relation estimates and in assigning related probabil­ity estimates so that internal mathematicalconsistency is always maintained.

Another issue is whether or not to introduce abias into risk estimates. In the practical application ofrisk measurement, it is not unusual for"conservative"risk estimates to be chosen for a wide variety of eco­nomic or financial events. The person in charge of riskmeasurement often believes that the only properresponse is to err on the side of caution when measur­ing risks. Unfortunately, when this type of conserva­tism is practiced for measuring risks in an investmentprocess, the outcome will be very substandard returnsrelative to the actual risks taken. The conservative biasin the risk measurement process will translate, as apractical matter, into an unnecessary reduction inrisk-bearing capacity, which, in tum, will limit returnopportunities compared with an investment processbased on internally consistent, fair, and unbiased esti­mates of future risks.

The price of reducing risks is also important tothe risk management process. As Lo discusses, onecan often observe explicit prices for certain types offinancial hedging transactions, or various versions ofoption pricing theory can allow one to estimate theprice of a certain type of financial hedging transac­tion. Obviously, for an economic system, consideringthe price of reducing risk is essential.

What many analysts forget is that one should notstop at analyzing the price of hedging a single trans­action. One can also reduce risk at the level of thewhole portfolio. In this case, correlations between anytwo pairs of financial positions matter a great deal indetermining whether a lower price for minimizingrisks can be obtained at the portfolio level or at thetransaction level. In most practical cases, correlationsare such that significant reductions in the price oflimiting risk may be obtained when they are viewedat the portfolio level instead of the transaction level.

Once probabilities and prices are on the table,thinking about preferences is much easier. What isimportant is that the assumption of symmetry inpreferences should be explicitly recognized and

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explored. Is there something in the nature of theinvestor or the investment problem that suggests thatrisk-bearing capacity should be different for gainsand losses? Behavioral finance indicates that in manycases, people do express an asymmetry of prefer­ences. In financial theory, the building block of putand call options allows a rich approach to tailoringportfolios to match the asymmetry in preference, butat a cost. As a result, one is explicitly forced to thinkconsistently and simultaneously in terms of probabil­ities, prices, and preferences to get a full understand­ing of risk management.

Measuring vs. Managing with VARTo use VAR approaches effectively in the risk man­agement process and as part of the investment pro­cess, one needs a very thoughtful and completeunderstanding of the limits of VARas a risk measure­ment tool, which is not to say that VARis not a criticaltool in the risk management process. But as with anytool, especially quantitative tools, one needs to knowits limits to use it properly. Michele McCarthy pro­vides a thorough examination of VAR, noting care­fully its advantages and disadvantages.

Several characteristics of VAR analysis, as com­monly used, need highlighting. First, VAR is generallycalculated using short-run, historical, daily data. Thiscommon habit has some unappreciated side effects.

Daily data, for example, introduce the likelihoodof underestimating correlations, especially in globalportfolios. This underestimation occurs because mar­kets in different continents and time zones close atdifferent times. Financially important informationmay become available after one market closes butbefore another closes on the same day. Closing-dayprices will show a discrepancy because of informa­tion availability in certain time zones that gets cor­rected the next day when the market reopens. Theresult is lower correlations in the prices of daily datathan are truly the case. Using weekly or monthly datato calculate correlations goes a long way toward min­imizing this problem. Two-day averaging is a verycrude first step that addresses the problem in a min­imal way, but it is a start. A low estimate of correla­tions results in an overdependence on diversificationthat may be an illusion.

Daily data, when used for global portfolios, areplagued with holidays. The common habit is to usethe previous day's closing price during the holidayperiod until the market in question reopens for trad­ing. This process lowers estimated correlations aswell as volatility. When short periods are analyzed,such as the past 100 days, the biases that are intro­duced through the use of daily data can matter a lot.

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Introduction to Risk Management

Using commonly calculated historical VAR mea­sures in a portfolio-construction process runs into thedanger of mixing forward-looking judgments aboutreturns with backward-looking estimates of risk. Forexample, fixed-income markets were quite calm in theUnited States in 1993, when the U'S. Federal Reservekept its federal funds rate locked at 3 percent all year.Price volatility declined for fixed-income markets, asmeasured with historical daily data, throughout 1993.Thus, using historically based VAR estimates for riskput one in the position of seeing lower and lower risks,even as the true risks of a Federal Reserve tighteningand a bond market collapse were increasing. Theworst case hit in February of 1994, when historical­based VAR signals were still showing relatively lowrisks in the fixed-income sector.

The issue involves the potential for risk to bemean reverting. That is, if high-risk periods are fol­lowed by lower risk periods and vice versa, thenhistorical VAR measures may well regularly sendlow-risk signals just before financial storms and sendhigh-risk signals after storms and before the calmingperiods. One needs to use some judgment in thesecases, and the naive assumption that the recent pastwill repeat itself is probably a very poor assumption.One can also build quantitative systems that usehistorical data in a more appropriate and dynami­cally adjusting fashion to gain some improvedinsights into future risks. Even better, one can intro­duce return-forecasting systems and processes intothe risk-estimation process. Changes in both returnforecasts and factors influencing returns can haveimportant, forward-looking implications for estimat­ing risks.

Another limitation of VAR, as commonly used,is its inability to deal with option positions, whetherexplicit positions or embedded in structured posi­tions. Options are a wonderful way of capturingasymmetric risks. Symmetric risk measures, such ascommon uses of VAR, are handicapped when option­related positions are important in a portfolio. Andembedded options are more common than manyinvestors realize.

For example, high-yield bonds are best analyzedas put options. The lender (investor) is writing (short)a put option on the assets of the company. If every­thing goes well, the company repays the loan onschedule with the agreed-on interest. If everythinggoes badly, the lender ends up owning the assets ofthe company just when those assets have signifi­cantly less value than when the loan was made. Whatthis example clearly argues is that one needs anoption-theoretic approach to estimating the probabil­ities of default. Some path-breaking quantitativework has been done in this regard by the KMV Cor­poration, the results of which are discussed byStephen Kealhofer.

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Risk Management: Principles and Practices

In addition, equities are like call options, partic­ularly in entrepreneurial companies with short trackrecords, tremendous potential, and little profits. Theinvestor pays an up-front fee for the stock and isbetting on everything going well in the long run andon the entrepreneurial company developing into thenext Microsoft or Federal Express. In the case ofhigh-yield bonds (put options) and equity in youngcompanies (call options), the option-theoreticapproach to risk measurement focuses attention onthe volatility of the underlying cash flows and thevalue of the assets. In these cases, going beyond VARto estimate forward-looking risks is essential to cap­ture the risk asymmetry embedded in these option­like positions.

Rare events also cause problems for the VARmethodology. One tends to use the recent past in theVAR calculation, and this practice may ignore somevery big and risky past events. The obvious supple­ment is to look to scenario tests and Monte Carlosimulations to help capture the risk involved in rarelyoccurring events and financial shocks.

Rare events are complicated by the likelihoodthat, within a given asset class, the correlationsbetween exposures tend to rise, and rise sharply tounity, in a crisis situation. An example of this"increasing correlations in a crisis" problem was thecredit and liquidity crisis of the summer of 1998. Onecan argue that what brought down the investmentfirm of Long-Term Capital Management (LTCM) wasthat its long (leveraged) positions in the credit mar­kets were normally lowly correlated, but in the crisis,volatilities and correlations rose sharply, makingLTCM's portfolio much riskier than standard, histor­ically based models would have suggested before thecrisis. There are, of course, other reasons for LTCM'sproblems, and many more subtleties and caveatssurrounding the episode, as Richard Bookstaber dis­cusses in his presentation.

To close this discussion of VAR on a more posi­tive note, one of the key advantages of any VAR­based approach to risk measurement is that it focuseson the portfolio and not on individual trades. Assuch, VAR introduces directly into the process anappreciation of correlations and the power of diver­sification as a risk-reducing tool. Single position risk­estimation techniques, such as option pricing, do nothave this ability, and as a result, they miss the powerof correlation analysis that is captured automaticallyin VAR approaches.

The Geometry of Risk andCorrelationOne of the factors that is absolutely critical to effec­tively integrating risk measurement techniques into

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the investment process is using the intuition pro­vided by different risk measures to gain insights intomanaging risks. Some interesting visual aids can helpgreatly in the process of converting risk measure­ments into judgment and intuition.

Over the years, Ronald Layard-Liesching, theresearch director at Pareto Partners, has explored theways that mathematicians can display volatility andcorrelation in a spatial context. At Brinson Partners,much valuable work has been done on making risksand correlations more intuitive through using simplegeometry, as Brian Singer illustrates in his presenta­tion.

A number of intuitive ideas can be developedfrom some simple geometrical concepts. Basically,one visualizes volatility (such as standard deviation)as length (inches) and correlations as angles (cosineof the correlation coefficient). Putting two portfoliostogether in this way generates an intuitive visualiza­tion of the power of correlations.

For example, if an investor buys $100 of the S&P500 as the benchmark portfolio and then adds anoverlay portfolio, what is the total risk of the twoportfolios? Suppose the risk of the S&P 500 portfoliois estimated at 16 percent. (It has been measuredsomewhat lower in the recent bull market of 1993­1999.) Now, consider three different overlay portfo­lios. The first is a $50 hedge (short S&P futures, forexample). The correlation (angle) between the bench­mark and the hedge is -1.0 (perfect hedge). The inves­tor can draw a line 16 inches long for the benchmarkand then retrace (an angle of 0 degrees) 8 inches torepresent the 50 percent hedge. The total risk is 8percent, or 8 inches.

The second overlay involves leverage, in whichthe investor borrows $50 and invests that $50 into theS&P 500 as well. The correlation (angle) between thebenchmark and the leveraged overlay is 1.0 (perfect).The investor can draw a line 16 inches long to repre­sent the benchmark and then keep drawing foranother 8 inches to represent the overlay. The angleis 180 degrees, and the total risk is 24 percent, or 24inches.

For the more interesting case of market neutral­ity, the overlay is constructed with $50 of supportingcapital and 8 percent of risk in a way that makes itlikely that the overlay will have zero correlation withthe S&P 500. Zero correlation is represented by anangle of 90 degrees. The investor draws a line 16inches long to represent the benchmark and then atthe end of that line, the investor draws a perpendic­ular line 8 inches long to represent the market-neutraloverlay. The line that completes a right-angle triangle(i.e., the hypotenuse) represents the total risk of the

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combined portfolios. By using the Pythagorean The­orem, the investor can calculate total risk as thesquare root of the sum of 16 squared plus 8 squared.That is, total risk is the square root of 320 (256 + 64),or 17.89 percent. Note that the 8 percent risk overlayadds only 1.89 percent of additional risk to the totalrisk of the combined portfolios relative to the 16percent risk of the benchmark portfolio. If the excessreturn potential of the overlay portfolio has any kindof reasonable risk-return trade-off (informationratio, that is), then the incremental excess returnpotential is a bargain relative to the incremental riskin the total (combined) portfolio.

By contrast, if the overlay portfolio has a correla­tion of 0.71with the benchmark, the investor will needto draw a line at 135 degrees (45 degrees for -0.71correlation) that extends total risk in a way that ismuch more similar to the leveraged example. In thiscase, the investor will see some total risk reductionrelative to the leverage example, but not very much,especially when compared with the market-neutraloverlay example. Unfortunately, most u.s. equitymanagers try to outperform the S&P 500 by runninga portfolio of under- and overweights relative to theS&P 500 that is highly correlated with the index, andthey fail to take advantage of the risk-reducing prop­erties of designing market-neutral overlays. As moreand more investors understand and appreciate theintuition offered by the geometry of risk, they maywell start to demand that their asset managers activelymeasure the correlation of the implicit overlay portfo­lio to the benchmark portfolio and, eventually,demand that managers design portfolios that ex anteare expected to have zero or negative correlations tothe benchmark yet still earn a reasonable excess returnfor the risks being taken.

Managing Operational RisksAlthough much risk measurement and risk manage­ment attention is focused on the investment process,asset management companies probably face at least asmuch risk in terms of how they manage their complexand interrelated fiduciary and regulatory responsibil­ities. In actuality, asset management companies arerelatively complex organizational structures. Thiscomplexity can be appreciated when one tries to tracethe whole process from making an investment deci­sion to reconciling the trade, reporting results to cli­ents, marketing to clients, and meeting the hugeburden of regulatory reporting and complex rules fordifferent types of investment structures. Indeed, usingthe terms of industrial organization theory, asset man­agement companies face both "interactive complex­ity" (i.e., they have a high degree of interrelatedprocesses) and "tight coupling" (i.e., many importantprocesses are linked in a critical path to each other).

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Introduction to Risk Management

Both of these traits, when they occur in concentratedforms, are known to increase the probability of oper­ational risks. In tum, operational risks, much morethan poor investment performance, can put the assetmanagement company in legal or regulatory jeop­ardy. Robert McLaughlin discusses some of the legalissues of being a fiduciary institution.

From a practical point of view, asset manage­ment companies can take a number of steps to reducethe severity of fiduciary and operational risks. Thefirst step is to simplify internal reporting lines, wherepossible, taking care to tightly link responsibilitywith accountability and with decision-makingauthority. These organizational and cultural changeshelp reduce the operational risks of complex organi­zations.

In addition, asset management companies canlearn something from the corporate finance literatureconcerning the use of incentives in corporations.Indeed, asset management companies can learnmany lessons from corporate finance theory, some ofwhich Charles Smithson discusses.

One of the interesting subjects for examination isthe use of incentive compensation. In the corporateworld, some evidence exists that bonuses related tostock options can increase risk-taking incentives rel­ative to cash or stock payments. This idea makessome sense, given that high volatility raises the valueof a given option contract, everything else beingequal.

Another key element that links operational risksand compensation is the willingness of a company toinvest in human capital. Ifasset management compa­nies make a commitment to employee training­meaning all the employees (in the back office, in clientservice, etc.), not just portfolio managers-then theemployees will get a keen sense of support from theparent institution and understand that they are notjust earning a salary but that the company is investingin their personal future. Operational risk benefits arederived from employee education as well. For exam­ple, the better the back-office personnel understandthe investment process, the more likely they willcatch trading errors and more efficiently reconciletrades and notice mistakes in net asset value calcula­tions. In short, operational risk management startswith developing straightforward business processes,but it also includes how the company compensatesand invests in its employees-with money and withtraining.

Risk Management to EnhanceReturnsRisk management has gone through a number ofphases of development in the asset management

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RiskManagement: Principles and Practices

world. Phase one focused on risk measurement, notrisk management. At first, risk measurement toolswere not integrated into the portfolio constructionprocess, but as the clients of asset management ser­vices increasingly focused on the excess returns beingearned relative to the risks being taken (i.e., the infor­mation ratio), there has been a strong desire to moveinto phase two: integrating risk management into theinvestment process.

Two authors in this proceedings share some spe­cial insights on going beyond risk measurement tomaking risk management part of both the portfolio­construction and the overall asset-liability manage­ment process. One approach is to look at practicalimplementation issues, which are discussed byJacques Longerstaey. A very different perspective isprovided from the pension fund point of view byDesmond Mac Intyre, who looks explicitly at theexperience of General Motors Investment Manage­ment Corporation in administering its retirementbenefit programs.

One point that emerges in almost every discus­sion of risk management is that taking some of theuseful, but always flawed, tools of risk measurement

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and integrating them into the investment processrequires judgment. Risk measurers are notorious foravoiding explicit judgments, but even risk measure­ment tools have critical built-in assumptions thatsimplify the world, sometimes in very misleadingways. Risk managers who are actively involved in therisk-return calculus that is the essence of construct­ing efficient portfolios know that forward-lookingjudgment is always going to be a key element.

The message is that, as asset managers, weshould not be focused on the elusive search for theHoly Grail of risk measurement-the one numberthat summarizes our total risk position. Instead, wemust focus on making sure we pay attention to all thecomponents of the portfolio process: excess returnexpectations, risk estimates, and correlation esti­mates. Historically, we may have spent too muchtime on returns, not enough time on risk, and notremotely enough time thinking about the implica­tions of correlations. If we can get more balance intoour investment process, then there is a strong likeli­hood that we can effectively use risk management toenhance excess returns relative to the risks beingtaken.

©Association for Investment Management and Research

A Framework for Understanding MarketCrisisRichard M. BookstaberHead of Risk ManagementMoore Capital Management

The key to truly effective risk management lies in the behavior of markets during timesof crisis, when investment value is most at risk. Observing markets under stress teachesimportant lessons about the role and dynamics of markets and the implications for riskmanagement.

N o area of economics has the wealth of data thatwe enjoy in the field of finance. The normal

procedure we apply when using these data is tothrowaway the outliers and focus on the bulk of thedata that we assume will have the key informationand relationships that we want to analyze. That is, ifwe have 10 years of daily data-2,500 data points­we might throw out 10 or 20 data points that aretotally out of line (e.g., the crash of 1987, the problemsin mid-January 1991during the Gulf War) and use therest to test our hypotheses about the markets.

If the objective is to understand the typical day­to-day workings of the market, this approach may bereasonable. But if the objective is to understand therisks, we would be making a grave mistake. Althoughwe would get some good risk management informa­tion from the 2,490 data points, unfortunately, thatinformation would result in a risk managementapproach that works almost all the time but does notwork when it matters most. This situation has hap­pened many times in the past: Correlations thatlooked good on a daily basis suddenly went wrong atexactly the time the market was in turmoil; value atrisk (VAR) numbers that tracked fairly well day byday suddenly had no relationship to what was goingon in the market. In the context of effective risk man­agement, what we really should do is throw out the2,490 data points and focus on the remaining 10because they hold the key to the behavior of marketswhen investments are most at risk.

This presentation considers the nature of themarket that surrounds those outlier points, the pointsof market crisis. It covers the sources of market crisisand uses three case studies-the equity market crash

© 1999 Richard M. Bookstaber

of 1987, the problems with the junk bond market inthe early 1990s, and the recent problems with Long­Term Capital Management (LTCM)-to illustrate thenature of crisis and the lessons for risk management.This presentation also addresses several policy issuesthat could influence the future of risk management.

Sources of CrisisThe sources of market crisis lie in the nature and roleof the market, which can be best understood bydeparting from the mainstream view of the market.

Market Efficiency. The mainstream academicview of financial markets rests on the foundation ofthe efficient market hypothesis. This hypothesisstates that market prices reflect all information. Thatis, the current market price is the market's "bestguess" of where the price should be. The guess maybe wrong, but it will be unbiased; it is as likely to betoo high as too low. In the efficient market paradigm,the role of the markets is to provide estimates of assetvalues for the economy to use for planning and cap­ital allocation. Market participants have informationfrom different sources, and the market provides amechanism that combines the information to createthe full information market price. Investors observethat price and can plan efficiently by knowing, fromthat price, all of the information and expectations ofthe market.

A corollary to the efficient market hypothesis isthat, because all information is already embedded inthe markets, no one can systematically make moneytrading without nonpublic information. If new publicinformation comes into the market, the price will

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RiskManagement: Principles and Practices

instantaneously move to its new fair level beforeanybody can make money on that new information.At any point in time, just by luck, some traders willbe ahead in the game and some will be behind, but inthe long run, the best strategy is simply to buy andhold the overall market.

I must confess that I never felt comfortable withthe efficient market approach. As a graduate studentwho was yet to be fully indoctrinated into this para­digm, I could look at the many simple features of themarket that did not seem to fit.

Why do intraday prices bounce around as muchas they do? The price of a futures contract in thefutures market or a stock in the stock market movesaround much more than one would expect from newinformation coming in. What information could pos­sibly cause the price instantaneously to jump twoticks, one tick, three ticks, two ticks second by secondthroughout the trading day?

How do we justify the enormous overhead ofhaving a continuous market with real-time informa­tion? Can that overhead be justified simply on thebasis of providing the marketplace with priceinformation for planning purposes? In the efficientmarket context, what kind of planning would peoplebe doing in which they had to check the market andinstantly make a decision on the basis of a tick up ordown in price?

Liquidity and Immediacy. All someone has todo is sit with a broker/dealer trader to see that morethan information is moving prices. On any given day,the trader will receive orders from the derivativedesk to hedge a swap position, from the mortgagedesk to hedge out mortgage exposure, and from cli­ents who need to sell positions to meet liabilities.None of these orders will have anything to do withinformation; each one will have everything to do witha need for liquidity.

And the liquidity is manifest in the trader's ownactivities. If inventory grows too large and the traderfeels overexposed, the trader will aggressively hedgeor liquidate a portion of the position, and the traderwill do so in a way that respects the liquidity con­straints of the market. If the trader needs to sellZ,OOObond futures to reduce exposure, the trader does notsay, "The market is efficient and competitive, and myactions are not based on any information aboutprices, so I will just put those contracts in the marketand everybody will pay the fair price for them." If thetrader puts 2,000 contracts into the market all at once,that offer obviously will affect the price, even thoughthe trader does not have any new information.Indeed, the trade would affect the market price evenif the market knew the trader was selling without anyinformational edge.

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The principal reason for intraday price move­ment is the demand for liquidity. A trader is uncom­fortable with the level of exposure and is willing topay up to get someone to take the position. The moreuncomfortable the trader is, the more the trader willpay. The trader has to pay up because someone elseis getting saddled with the risk of the position­someone who most likely did not want to take on thatposition at the existing market price because other­wise, that person would have already gone into themarket to get it.

This view of the market is a liquidity view ratherthan an informational view. In place of the conven­tional academic perspective of the role of the market,in which the market is efficient and exists solely forinformational purposes, this view is that the role of themarket is to provide immediacy for liquidity demand­ers. The globalization of markets and the Widespreaddissemination of real-time information have madeliquidity demand all the more important. With moreand more market information disseminated to a widerand wider set of market participants, less opportunityexists for trading based on an informational advan­tage, and the growth of market participants meansthere are more incidents of liquidity demand.

To provide this immediacy for liquidity demand­ers, market participants must exist who are liquiditysuppliers. These liquidity suppliers must have freecash available, a healthy risk appetite, and risk man­agement capabilities, and they must stand ready tobuy and sell assets when a participant demands thata transaction be done immediately. By accepting thenotion that markets exist to satisfy liquidity demandand liquidity supply, the framework is in place forunderstanding what causes market crises, which arethe times when liquidity and immediacy matter most.

Liquidity Demanders. Liquidity demanders aredemanders of immediacy: a broker/ dealer who needsto hedge a bond purchase taken on from a client, apension fund that needs to liquidate some stock posi­tion because it has liability outflow, a mutual fundthat suddenly has some inflows of cash that it has toput into the index or the target fund, or a trader whohas to liquidate because of margin requirements orbecause of being at an imposed limit or stop-loss levelin the trading strategy. In all these cases, the definingcharacteristic is that time is more important thanprice. Although these participants may be somewhatprice sensitive, they need to get the trade done imme­diately and are willing to pay to do so. A huge bondposition can lose a lot more if the bondholder hagglesabout getting the right price rather than if the bond­holder just pays up a few ticks to put the hedge on.Traders who have hit their risk limits do not have anychoice; they are going to get out, and they are not in a

good position to argue whether or not the price is rightor fair. One could think of liquidity demanders as theinvestors and the hedgers in the market.

Liquidity Suppliers. Liquidity suppliers meetthe liquidity demand. Liquidity suppliers have aview of the market and take a position in the marketwhen the price deviates from what they think the fairprice should be. To liquidity suppliers, price mattersmuch more than time. For example, they try to takea cash position or an inventory position that theyhave and wait for an opportunity in which the liquid­ity demander's need for liquidity creates a diver­gence in price. Liquidity suppliers then provide theliquidity at that price.

Liquidity suppliers include hedge funds andspeculators. Many people have difficulty under­standing why hedge funds and speculators exist andwhy they make money in an efficient market. Theirwork seems to be nothing more than a big gamblingenterprise; none of them should consistently makemoney if markets are efficient. If they did have aninformational advantage, it should erode over time,and judging by their operations, most speculatorsand traders do not have an informational advantage,especially in a world awash in information.

So, why do speculators and liquidity suppliersexist? What function do they provide? Why do, orshould, they make money? The answer is that theyprovide a valuable economic function. They invest intheir business by keeping capital readily available forinvestment and by applying their expertise in riskmanagement and market judgment. They want tofind the cases in which a differential exists in priceversus value, and they provide the liquidity. In short,they take risk, use their talents, and absorb the oppor­tunity cost of maintaining ready capital. For this func­tionality, they receive an economic return.

The risk of providing liquidity takes severalforms. First, a trader cannot know for sure that a pricediscrepancy is the result of liquidity demand. Thediscrepancy could be caused by information or evenmanipulation. But suppose somebody waves a whiteflag and announces that they are trading strictlybecause of a liquidity need; they have no special infor­mation or view of the market and are willing to dis­count the price an extra point to get someone to takethe position off their hands. The trader who buys theposition still faces a risk, because no one can guaran­tee that between the time the trader takes on theposition and the time it can be cleared out the pricewill not fall further. Many other liquidity-driven sell­ers may be lurking behind that one, or a surpriseeconomic announcement might affect the market.

The liquidity supplier should expect to makemoney on the trade, because there is an opportunity

A Framework for Understanding Market Crisis

cost in holding cash free for speculative opportuni­ties. The compensation should also be a function ofthe volatility in the market; the more volatile themarket, the higher the probability in any time periodthat prices will run away from the liquidity suppliers.In addition, their compensation should be a functionof the liquidity of the market; the less liquid themarket, the longer they will have to hold the positionand thus the longer they will be subject to the vola­tility of the market.

Interaction of Liquidity Supply and Demandin a Market Crisis. A market behaves qualitativelydifferently in a market crisis than in "normal" times.This difference is not a matter of the market being"more jumpy" or of a lot more news suddenly flood­ing into the market. The difference is that the marketreacts in a way that it does not in normal times. Thecore of this difference in behavior is that market pricesbecome countereconomic. The normal economic con­sequence of a decline in market prices is that fewerpeople have an incentive to sell and more people havean incentive to buy. In a market crisis, everything goesthe wrong way. A falling price, instead of deterringpeople from selling, triggers a growing flood of sell­ing, and instead of attracting buyers, a falling pricedrives potential buyers from the market (or, evenworse, turns potential buyers into sellers). This out­come happens for a number of related reasons: Sup­pliers who were in early have already committed theircapital; suppliers turn into demanders because theyhave pierced their stop-loss levels and must liquidatetheir holdings; and others find the cost of business toohigh with widening spreads, increased volatility, andreduced liquidity making the risk-return trade-offs ofmarket participation undesirable. It is as if the marketis struck with an autoimmune disease and is attackingits own system of self-regulation.

An example of this drying up of supply can beseen during volatility spikes. Almost every year insome major market, option volatilities go up to a levelthat no rational person would think sustainable. Dur­ing the Asian crisis in 1998, equity market volatilityin the United States, Hong Kong, and Germany morethan doubled. During the exchange rate crisis in Sep­tember 1993, currency volatility went up manyfold.During the oil crisis that accompanied the Gulf War,oil volatilities exceeded 80 percent. Volatilities forstocks went from the mid-teens to more than 100percent in the crash of 1987. Did option traders reallythink stock prices would be at 100 percent volatilitylevels during the three months following the crash?Probably not. But the traders who normally wouldhave been available to take the other side of a tradewere out of the market. At the very time everybodyneeded the insurance that options provide and was

9

RiskManagement: Principles and Practices

willing to pay up for it, the people who could sell thatinsurance were out of the market. They had already"made their move," risking their capital at muchlower levels of volatility, and now were stopped outof their positions by management or, worse still, hadlost their jobs.

Even those who still had their jobs kept theircapital on the sidelines. Entering the market in the faceof widespread destruction was considered impru­dent, and the cost of entry was (and still is) fairly high.Information did not cause the dramatic price volatil­ity. It was caused by the crisis-induced demand forliquidity at a time that liquidity suppliers wereshrinking from the market.

Market Habitat. All investors and traders havea market habitat where they feel comfortable tradingand committing their capital-where they know themarket, have their contacts in the market, have a feelfor liquidity, know how the risks are managed, andknow where to look for information. The habitat maybe determined by an individual's risk preferences,knowledge, experience, time frame and institutionalconstraints, and by market liquidity. Investors willroam away from their habitat only if they believeincremental returns are available to them. Someonewho is used to trading in technology stocks will needmore time for evaluation and a better opportunity totake a position in, say, the automotive sector, than inthe more familiar technology sector.

Nowadays, the preferred market habitat for mostinvestors and traders is expanding because of lowbarriers to entry and easy access to information. Any­one can easily set up an account to trade in manymarkets, ranging from the G-7 counties to the emerg­ing markets. Anyone can get information-often real­time information---on a wide variety of bonds andstocks that used to be available only to professionals.The days of needing to call a broker to check up on theprice of a favorite stock now seem a distant memory.

More information and fewer barriers to entryexpand habitat. Higher levels of risk also tend toexpand habitat. The distinction among assets blurs asrisk increases. In addition, market participantsbecome more like one another, which means thatliquidity demanders all demand pretty much the sameassets and grab whatever sources of liquidity are avail­able. This situation is characterized in the market as"contagion," but in my view, what is happening is anexpansion of habitat because the risk of the market hasmade every risky asset look pretty much the same. Ifall investors are in the same markets, they will run intotrouble at the same time and will start liquidating thesame markets to get financing and reduce their risks.

Think of how the investor's focus shifts as theinvestor moves from a normal market environment

10

to a fairly energetic market environment, and then toa crash environment. In a normal market, investorshave time to worry about the little things: the earn­ings of this company versus that company, P/Es,dividends, future prospects, and who is managingwhat. As the energy level goes up in the market,investors no longer have the luxury of consideringthe subtleties of this particular stock or that stock.They need to concentrate on sectors. If the technologysector is underperforming, all technology stocks lookthe same. If oil prices go up, an oil company's man­agement and earnings prospects no longer matter; allthat matters is that the company is in the energysector. Turn the heat up further to a crash environ­ment and all that participants care about is that it isa stock and that they can sell it. All stocks look thesame, and the correlations get close to 1.0because theonly characteristic that matters is that this asset is astock or, for that matter, is risky. In fact, the situationcan get even worse; junk bonds may be viewed to besimilar enough to stocks that they trade like stocks.The analysis and market history of the normal marketenvironment no longer applies. The environment isdifferent; the habitat has changed.

An analogy from high-energy physics helps toillustrate the situation. As energy increases, the con­stituents of matter blur. At low energy levels-roomtemperature-molecules and atoms are distinct anddifferentiated. As energy goes up, the moleculesbreak apart and what is left are the basic buildingblocks of matter, the elements. As energy goes upeven more, the atoms break apart and plasma is left.Everything is a defused blob of matter.

As the energy of the market increases, the sametransformation happens to the constituents of themarket. In a market crisis, all the distinct elements ofthe market-the stocks (e.g., IBM and Intel), the mar­ket sectors (e.g., technology and transportation), theassets (e.g., corporate bonds and swap spreads)-turninto an undifferentiated plasma. Just as in high­energy physics, where all matter becomes an undiffer­entiated "soup," in the high-energy state of a marketcrisis, all assets blur into undifferentiated risk.

One of the most troubling aspects of a marketcrisis is that diversification strategies fail. Assets thatare uncorrelated suddenly become highly corre­lated, and all the positions go down together. Thereason for the lack of diversification is that in a high­energy market, all assets in fact are the same. Thefactors that differentiate them in normal times are nolonger relevant. What matters is no longer the eco­nomic or financial relationship between assets butthe degree to which they share habitat. What mattersis who holds the assets. If mortgage derivatives areheld by the same traders as Japanese swaps, these

two types of unrelated assets will become highlycorrelated because a loss in the one asset will forcethe traders to liquidate the other. What is most dis­turbing about this situation is not that the carefulformulation of an optimized, risk-minimizing port­folio turns to naught but that there is no way todetermine which assets will be correlated withwhich other assets during a market crisis. That is, notonly will diversification fail to work at the very timeit is most critical, but determining the way in whichit will fail will be impossible.

Liquidity demanders use price to attract liquiditysuppliers, which sometimes works and sometimesdoes not. In a high-risk or crisis market, the drop inprices actually reduces supply and increases demand.This is the critical point that participants must lookfor. Unfortunately, most people never know how thinthe ice is until it breaks. Most people did not see anyindications in the market in early October 1987 orearly August 1998that made them think they were onthin ice and that a little more weight would dislocatethe market and prices would become an adverse sig­nal. Of course, the indications seem obvious after thefact, but it should suggest something about the com­plexity of the market that these indications are misseduntil it is too late. For example, option prices, partic­ularly put option prices, were rising before the crashof 1987.After the crash, this phenomenon was pointedto as an indicator that there was more risk inherent inthe market and more demand for protection. In themonth or so before Long-Term Capital Management(LTCM) had its problems, the U.S. swap spread wasat its lowest volatility level in a decade. This lowvolatility demonstrated a lack of liquidity and com­mitment to the swap market. In the case of the 1987market crash, the missed indicator was high volatility;in the case of the LTCM crisis, the missed indicatorwas low volatility.

Case StudiesThree case studies help to demonstrate the nature ofmarket crises: the equity market crash of 1987, thejunk bond crisis, and the LTCM default.

1987 Equity Market Crash. The market crashof 1987 occurred on Monday, October 19. But it wasset up by the smaller drop of Friday, October 16 andby the reaction to that drop from a new and popularstrategy-portfolio insurance hedging.

Portfolio insurance is a strategy in which a man­ager overlays a dynamic hedge on top of the invest­ment portfolio in order to replicate a put option.Operationally, the hedge is reduced as the portfolioincreases in value and increased as the portfoliodeclines in value. The hedge provides a floor to the

A Framework for Understanding MarketCrisis

portfolio, because as the portfolio value dropsbeyond a prespecified level, the hedge increases tothe point of offsetting future portfolio declines onefor one. The selling point for portfolio insurance isthat it provides this floor protection while retainingupside potential by systematically reducing thehedge as the portfolio rises above the floor.

This hedging strategy is not without a cost.Because the hedge is being reduced as the portfoliorises and increased as the portfolio drops, the strategyessentially requires buying on the way up and sellingon the way down. The result is a slippage or frictioncost because the buying and selling happen in reac­tion to the price moves; that is, they occur slightlyafter the fact. The cumulative cost of this slippage canbe computed mathematically using the tools ofoption-pricing theory; the cumulative cost of the slip­page should be about the same as the cost of a putoption with an exercise price equal to the hedge floor.

The key requirement for a successful hedge, andespecially a successful dynamic hedge, is liquidity. Ifthe hedge cannot be put on and taken off, then obvi­ously all bets are off. Although liquidity is not muchof a concern if the portfolio is small and the manageris the only one hedging with a particular objective, itbecomes a potential nightmare when everyone in themarket has the same objective, which in a nutshell iswhat happened on October 19.

On Monday morning October 19,everybody whowas running a portfolio insurance program looked atthe computer runs from Friday's market decline andsaw they had to increase their hedges. They had toshort out more of the exposure that they had to themarket, and the hedging instrument of choice was theS&P 500 Index futures contract. Shortly after the openon October 19, the hedges hit the S&P pit.

Time mattered and price did not; once their pro­grams were triggered, the hedge had to be increasedand an order was placed at the market price. And alot of programs were triggered. Portfolio insurancewas first introduced by LOR (Leland O'Brien Rubin­stein) in 1984, and portfolio insurance programswere heavily and successfully marketed to pensionfunds, which overlaid tens of billions of dollars ofequity assets.

The traders in the S&P pit are very fast at execu­tion. When someone wants to sell a position at themarket, a trader in the pit will buy it immediately.Once the market maker takes the position, the marketmaker will want to take the first opportunity to getrid of it. The market makers on the floor make moneyon the bid-offer spread (on turnover) and not byholding speculative positions. Among the sourcesthey rely on to unload their inventory are programtraders and cash futures arbitrageurs. The program

11

RiskManagement: Principles and Practices

traders and arbitrageurs buy S&P contracts from thefutures pit while selling the individual stocks thatcomprise the S&P 500 on the NYSE. If the price of thebasket of stocks differs from the price of the futuresby more than the transaction costs of doing this trade,then they make a profit. This trade effectively trans­fers the stock market activities of the futures pit to theindividual stocks on the NYSE. It is here where thingsbroke down in 1987,and they broke down for a simplereason: Although the cash futures arbitrageurs, pro­gram traders, and market makers in the pit are all veryquick on the trigger, the specialists and equity inves­tors who frequent the NYSE are not so nimble.

The problem might be called "time disinterme­diation." That is, the time frame for being able to dotransactions is substantially different between thefutures market and the equity market. This situationis best understood with a stylized example. Supposethat you are the specialist on the NYSE floor for IBM.On Monday morning October 19, you wait for themarkets to open. Suddenly, a flood of sell orderscomes in from the program traders. You do not haveinfinite capital. Your job is simply to make the mar­ket. So, you drop the price of IBM a half a point andwait. Not many people are coming, so you drop it afull point, figuring now people will come.

Meanwhile, suppose I am an investment man­ager in Boston who is bullish on IBM, and I amplanning to add more IBM to my portfolio. I come in,glance at the screen, and see that IBM is down a halfpoint. After coming back from getting some coffee, Icheck again; IBM is now down a full point. The priceof IBM looks pretty good, but I have to run to mymorning meeting.

Half an hour has gone by, and you and the otherspecialists are getting worried. A flood of sell ordersis still coming in, and nowhere near enough buyersare coming in to take them off of your hands. Price isyour only tool, so you drop IBM another point andthen two more points to try to dredge up some buy­ing interest.

By the time I come back to my office, I notice IBMis down four points. If IBM had been down a halfpoint or a full point, I would have put an order in, butat four points, I start to wonder what is going on withIBM-and the market generally. I decide to wait untilI can convene the investment committee that after­noon to assess the situation.

The afternoon is fine for me, but for you, moreshares are piling into your inventory with every pass­ing minute. Other specialists are faced with the sameonslaught, and prices are falling all around you. Younow must not only elicit buyers, but you must alsocompete with other stocks for the buyers' capital. Youdrop the offer price down 10 points from the open.

12

The result is a disaster. The potential liquidity sup­pliers and investment buyers are being scared off bythe higher volatility and wider spreads. And, moreimportantly, the drop in price is actually inducingmore liquidity-based selling as the portfolio insur­ance programs trigger again and again to increasetheir selling to add to their hedges. So, because oftime disintermediation and the specialist not havingsufficient capital, the price of IBM is dropped tooquickly, the suppliers are scared off, and the portfolioinsurance hedgers demand even more liquidity thanthey would have otherwise.

This IBM example basically shows what hap­pened in the crash of 1987. Demand for liquiditymoved beyond ignoring price and focusing on imme­diacy to actually increasing as a function of the dropin price because of the built-in portfolio insurancerules. Supply dried up because of the difference intime frames between the demanders and suppliers,which led prices to move so precipitously that thesuppliers took the drop as a negative signal. The keyculprit was the difference in the trading time framesbetween the demanders and the suppliers. If thesellers could have waited longer for the liquidity theydemanded, the buyers would have had time to reactand the market would have cleared at a higher price.

1991 Junk Bond Debacle. Junk bonds, ormore euphemistically high-yield bonds, were themainstay of many corporate finance strategies thatdeveloped in the 1980s. The best known use of high­yield bonds was in leveraged buyouts (LBOs) andhostile takeovers. Both of these strategies followedthe same course over the 1980s. They started as goodideas that were selectively applied in the most prom­ising of situations. But over time, more and morequestionable deals chased after the prospect of hugereturns, and judgment was replaced with avarice.The investment banks played more the role of cheer­leader than advisor, because they stood to gain nomatter what the long-term outcome and they had agrowing brood of investment banking mouths andegos to feed.

The size of the average LBO transaction peakedin 1987. But deal makers continued working to main­tain their historical volumes even as the universe ofleverageable companies declined. Volume was main­tained in part by lowering the credit quality thresh­old of LBO candidates. The failed buyout of UnitedAirlines in 1989 is one example of this situation,because airlines are cyclical and previously had notbeen considered good candidates for a highly leveredcapital structure. Leverage in the LBOs also increasedover the course of the 1980s. Cash flow multiplesincreased in 1987 and 1988, from the 5x range in 1984and 1985 to the lOx range in 1987 and 1988. This

increase turned out to be fatal for many companies.An earnings shortfall that is manageable at 5 timescash flow can lead to default if the investors pay 10times cash flow.

Although LBOs moved from larger to smallerdeals, hostile takeovers went after bigger game astime went on. The RJR debt of nearly $10 billionrepresented approximately 5percent of the high-yieldmarket's total debt outstanding. Many institutionshad limitations on the total amount of exposure theycould have to anyone name, which became a con­straint given the size of the RJRissues.

The justification for hostile takeovers was, start­ing in the mid-1970s, for the market value ofcompanies to be less than their replacement cost.Thus, after a hostile takeover, the acquirer could selloff the assets and inventories for more than the costof buying the company holding those assets. Theactivity of hostile takeovers-and possibly the threatof further takeovers-woke up the market to thedisparity between the market value and the replace­ment cost of companies' assets, and the gap closed by1990.The arbitrage plays implicit in hostile takeoversled to an improvement of market efficiency intextbook fashion, and the raison d'eire for the hostiletakeovers disappeared. But the hope for financialkillings remained and led to continued demand forthe leverage of high-yield bonds as ammunition tobag the prey.

The following scenario summarizes the life cycleof LBOs and hostile takeovers. With these financialstrategies still virgin territory, and with the first prac­titioners of the strategies the most talented and cre­ative, the profits from the first wave of LBOs andhostile takeovers made headlines. More investors andinvestment bankers entered into the market, andcredit quality and potential profitability werestretched in the face of the high demand for high-yieldfinancing. Rising multiples were paid for LBOs andwere accepted in hostile takeovers because of both thehigher demand for financing and the increase inequity prices. The result of the stretching into lower­quality deals and the higher multiples paid for thecompanies led to more defaults.

The defaults hit the market even harder than didthe earlier LBO and hostile takeover profits. Withina few short months, high-yield bonds were brandedas an imprudent asset class. In 1991, the high-yieldbond market was laid to waste. Bond spreads wid­ened fourfold, and prices plummeted. The impact ofthe price drop was all the more dramatic because,even though the bonds were not investment grade,investors had some expectation of price stability. Theimpact on the market was the same as having the U.S.stock market drop by 70 percent. As with the 1987

A Framework for Understanding Market Crisis

stock market crash, the junk bond debacle was notthe result of information but of a shift in liquidity.

In 1991, the California Insurance Commissionseized Executive Life. The reaction to this seizure wasmany faceted, and each facet spelled disaster for thehealth of the market. Insurance companies that hadnot participated in the high-yield bond market lob­bied for stricter constraints on high-yield bond hold­ings. It is difficult to know whether this action wasdone in the interest of securing the industry'S reputa­tion, avoiding liability for the losses of competitorsthrough guaranty funds, stemming further failures(such as Executive Life), or meeting the threat of fur­ther insurance regulation. Insurance companies wereanxious to stand out from their competitors in theirholdings of high-yield bonds and featured their min­imal holdings of junk bonds as a competitive market­ingpoint.

A number of savings and loans (S&Ls) seized onthe high-yield market as a source of credit disinterme­diation. Federal deposit guarantees converted theirhigh-risk portfolios into portfolios that were essen­tially risk free. The S&Linvestors captured the spreadbetween the bond returns and the risk-free returnprovided to the depositors. That this situation was acredit arbitrage at the government's expense becameclear in the late 1980s. The government respondedwith the Financial Institutions Reform, Recovery andEnforcement Act in 1989. This act not only barredS&Lsfrom further purchases of high-yield bonds, butit also required them to liquidate their high-yieldbond portfolios over the course of five years. Theprospect of the new regulation and stiffening of cap­ital requirements by the Federal Home Loan BankBoard led S&Ls to reduce their holdings even in early1989by 8 percent, compared with an increase in hold­ings in the previous quarter of 10 percent.

Investors reacted quickly to the weakness in thehigh-yield bond market. InJuly 1989,high-yield bondreturns started to decline, hitting negative returns.For investors who did not understand the risk ofhigh-yield bonds, the realization of negative returnsmust have been a rude wake-up call. Over the thirdquarter of 1989, the net asset value of high-yieldmutual funds declined by as much as 10 percent. Theimplications of erosion of principal-eoupled withmedia reports of the defaults looming in the high­yield market-led to Widespread selling.

As with any other financial market, the junkbond market had both liquidity suppliers and liquid­ity demanders. Some poor-quality junk bonds madeit to the market, which caused some investors whonormally would have been suppliers of liquidity tospurn that market because it was considered impru­dent. Consequently, financing was reduced. These

13

Risk Management: Principles and Practices

people then had financial problems, which demon­strated that junk bonds were imprudent and whichmeant more people went out of the market. So, theliquidity suppliers who were willing to take on thebonds became liquidity demanders. They wanted toget rid of their junk bonds, and the more the pricedropped, the more they wanted to get rid of their junkbonds. Junk bonds were less than 5 percent of theirportfolios, so owning junk bonds was not going toruin the entire portfolio, but they could have lost theirjobs. Suddenly, suppliers were disappearing andturning into demanders. The price drop created thewrong signal; it made the bonds look worse than theyactually were.

The junk bond crash of 1991 was precipitated byseveral junk-bond-related defaults. But the extent ofthe catastrophe was from liquidity, not default. Insti­tutional and regulatory pressure accentuated theneed for many junk bond holders to sell, and to sellat any price. Because the usual liquidity supplierswere in the position of now needing to sell, notenough capital was in the market to absorb the flow.The resulting drop in bond prices, rather than draw­ing more buyers into the market, actually increasedthe selling pressure, because the lower prices pro­vided confirmation that high-yield bonds were animprudent asset class. Regulatory pressure andsenior management concerns-not to mention losseson existing bond positions-vetoed what many trad­ers saw as a unique buying opportunity.

1998 LTCM Default. Long-Term Capital Man­agement is a relative-value trading firm. Relative­value trading looks at every security as a set of factorsand finds within that set of factors some factor that ismispriced between one security and another. Themanager then tries to hedge out all the other factorsof exposure so that all that is left is long exposure inthe factor in one security and short exposure in thefactor in another security. One security is cheaperthan the other, so the manager makes money. Ideally,in relative-value trading, the positions should be self­financing so that the manager can wait as long asnecessary for the two prices to converge. If a spreadtakes, say, three years to converge, that is no problemif the position is self-financed.

The most common relative-value trading isspread trading. Spread trading is attractive becauseall that matters is the relative value between the twoinstruments. This approach has great advantages foranalytically based trading because it is easier to deter­mine if one instrument is mispriced relative toanother instrument than it is to determine if an instru­ment is correctly priced in absolute terms. A relative­value trader can still get it right even with making anerroneous assumption, so long as that assumption

14

affects both instruments similarly. Another advan­tage of relative-value trading is that a relative-valuetrade is immune to some of the most unpredictablefeatures of the market. If a macroeconomic shock hitsthe market, it will affect similar instruments in asimilar way. Although both instruments might dropin price, the relative value of the two may remainunaffected.

One of the problems of relative-value trading,and of working with spread trades in particular,occurs because the spreads between instruments aretypically very small. These small spreads are a directresult of trading between two very similar instru­ments, where the variations between the prices arevery small. Although in the end the dollar risk maybe the same as an outright trade to put on this risk­and thereby get double-digit expected returns-therelative-value trader is usually highly leveraged.

Relative-value trading has other problems aswell. First, these very big positions are hard to liqui­date, and the newer, less-liquid markets are usuallythe very markets that exhibit the spread discrepan­cies. Yet these are the very markets where experienceis limited and observers have not seen the risks playedout over and over. Second, in a relative-value trade,the manager requires price convergence between thetwo assets in a spread position. Sooner or later thatconvergence should take place, but the manager doesnot know when and thus may have a long holdingperiod. Third, because of the myriad risks and smallspreads, the modeling in relative-value trading has tobe very precise; if a manager has $10 billion long inone instrument and $10billion short in another instru­ment and if the manager is off by 1 percent, then themanager stands to lose a lot of money.

In terms of relative-value trading at LTCM, thetraders were doing such things as buying LIBORagainst Treasuries, so they were short credit risk.They were buying emerging market bonds versusBrady bonds and mortgages versus Treasuries. Whilethey had the trades on, they decided to reduce theircapital. In the early part of 1998, LTCM returnednearly $3 billion of capital to its investors, reducingits capital base from about $7 billion to a little morethan $3 billion.

Normally, LIBOR, Treasuries, and mortgages­the markets that LTCM invested in-are very liquid.The liquidity that the traders at LTCM had, however,was lower than what they expected for several rea­sons, some completely unanticipated. Even in a nor­mal market environment, if a trader is dealing withreally large size, the market is not very liquid; if thetrader starts to sell, nobody wants to buy because theyknow there is a lot more supply where that came from.LTCM's real problems, however, started on July 7,

1998. On that day, the New York Times ran a story thatSalomon Smith Barney was closing its Ll.S, fixed­income proprietary trading unit. Even though I wasthe head of risk management at Salomon, I did notknow this decision had been made. I certainly ques­tioned the move after the fact on several grounds; theproprietary trading area at Salomon was responsiblefor virtually all the retained earnings of Salomon dur­ing the previous five years. Furthermore, this was anannouncement that no trader would ever want madepublic. Closing the trading unit meant that Salomon'sinventory would probably be thrown into the market.If Salomon was closing its proprietary trading area inthe United States, it probably would do so in Londonas well. So, the logical assumption was that Salomon'sLondon inventory would be coming into the marketas well. The result was that nobody would take theother side of that market; who wants to buy the first$100 million of $10 billion of inventory knowinganother $9.9billion will follow? Salomon should havequietly reduced its risk and exposure. Once the riskand exposure were down and inventory was low,then Salomon could have announced whatever itwanted. As it was, the nature of the announcementworked to dampen demand in the market, which didnot bode well for LTCM.

Another event that was not favorable for LTCMoccurred in August 1998;Russia started to have prob­lems. LTCM, like everybody else, had exposure toRussia. The result was that LTCM had to liquidateassets because its cash reserve was gone. Liquidatingassets is only a big deal when nobody wants theassets. Not only did nobody want the assets becauseof the glut of inventory resulting from the closing ofSalomon's proprietary trading units; they now didnot want the assets because they knew LTCM wasselling because it had financial problems and becausethey did not know how deep LTCM's inventory was.At the time LTCM was demanding immediacy,liquidity suppliers did not exist in the market.

To make matters worse, LTCM was itself a majorliquidity supplier in the market. LTCM was provid­ing the other side of the market for people whowanted to hedge out their credit exposure in variousinstruments. The reason LTCM was making moneywas that it was supplying liquidity. It was providinga side of the market that people needed. Once LTCMwas gone, not many other people were left. And thosewho were left were not going to stay in the face of thishuge overhang of supply. So, when LTCM had to sell,a market did not exist for its positions, because LTCMwas the market. LTCM's selling drove the price downenough so that, just as in the case of portfolio insur­ance, LTCM had to sell even more. LTCM did man­age to sell some of its positions but at such low prices

A Framework for UnderstandingMarket Crisis

that when it marked to market its remaining hold­ings, they dropped so much as to require even moremargin and to require even more selling. So, a cycledeveloped, and as the spreads widened, anybodywho would have provided liquidity on the other sidewas not willing to.

If people had had more time, the downwardcycle would have been halted; someone would havetaken the assets off LTCM's hands because the assetswere unbelievably mispriced, not only in terms ofprice levels but also in totally different directions.How could fixed-income instruments in Germanyhave almost historically low volatility while LIBORinstruments in the United Kingdom have historicallywide spreads? The issue was strictly one of liquidityand immediacy; buyers simplywere not there quicklyenough.

Many things have been written about LTCM,some of which are not very favorable to the principalsof the firm. But the fact is that the principals areamong the brightest people in finance. They havedone relative-value trading longer than anybody elseon Wall Street. The failure of LTCM says more aboutthe inherent risk and complexity of the market than itdoes about LTCM; the market is sufficiently complexthat even the smartest and most experienced can fail.Who would have anticipated a closing of U.S. fixed­income proprietary trading at Salomon? Who wouldhave anticipated that this closing would be revealedin a public announcement? Who would have antici­pated the speed and severity of the Russian debaclehard on the heels of the Salomon announcement? It isthat very complexity that the risk analysis modelsfailed to capture.

Lessons LearnedThese market crises share some common elementsthat can teach all of us important lessons about riskmanagement.

First, it is not just capital that matters. Whatmatters is the willingness to put that capital into themarket, to commit capital at times of crisis and highrisk. During the LTCM crisis, if somebody had beenwilling to commit capital at a time when the spreadswere at unbelievably wide levels, the crisis wouldhave been averted. I was in charge of risk manage­ment at Salomon Smith Barney at the time of thiscrisis and encouraged-unsuccessfully, it turnedout-a more aggressive position in the market.Salomon Smith Barney was in a position to stay inthese spread trades, because the firm had sizeablecapital and, through its proprietary trading group,more expertise on staff than anybody else in theworld. (Remember that LTCM was dubbed "SalomonNorth" because the bulk of its talent came from

15

RiskManagement: Principles and Practices

Salomon, but Salomon retained an exceptional talentfor relative-value trading even after John Meriwetherand others left the firrn.) Nevertheless, in spite of itsfar stronger capital position and its trading expertise,Salomon Smith Barney was just as quick to get out ofthe market as LTCM. So, what matters is not justcapital or expertise. What matters is capital andexpertise and the willingness to use that capital at thetime the market really needs liquidity.

Second, speculative capital is needed to meetliquidity demand. Either the markets must slowdown to allow people more time to respond to thedemand for immediacy, or more participants mustenter the markets who can act quickly and meet thatimmediacy. In the crash of 1987, circuit breakerswould have slowed things down so that the portfolioinsurance programs could have triggered at a pacethat the traders in New York and elsewhere couldhave matched. Or on the futures side, more specula­tors with capital could have made the market andheld onto those positions. Or on the stock exchangeside, specialists with more capital and staying powercould have held onto the inventory until the stockinvestors had gotten settled for the day.

Third, the markets must have differentiated par­ticipation. As the financial markets become more inte­grated, there is increasing focus on systemic risk-therisk inherent in the institutions that comprise thefinancial system. A nondifferentiated ecosystem hasa lot of systemic risk. One little thing goes wrong, andeverything dies. Complexity and differentiation arevaluable because if one little thing goes wrong, otherthings can make up for it. Systemic risk has its rootsin the lack of differentiation among market partici­pants. Modem portfolio theory focuses on the con­cept of diversification within a portfolio, which is finein a low-energy market. As a market moves to a high­energy state and habitats expand, what matters is notso much diversification among asset classes butdiversification among market participants.

If everything I hold is also held by other marketparticipants, all of whom have the same sort of port­folio and risk preferences that I have, I am not diver­sified. Ina low-energy state, this lack of diversificationwill not be apparent, because prices will be dictatedby macroeconomics and firm performance. As themarket moves to a high-energy state, things change.What matters then is which assets look like whichother assets based on the liquidity demanders andsuppliers who will be dumping assets into the market.So, in a low-energy state, I am well diversified, but ina high-energy state, everything goes against mebecause what matters now is not what the assets arebut the fact that they are pure risk and that they areall held by the same sort of people.

16

Finally, Wall Street has experienced a lot ofconsolidation-Citigroup and Morgan Stanley DeanWitter, for example. Big firms are sensitive to institu­tional and political pressure; they have to go throughmany checks and sign-offs and thus are slow to react.The habitat is becoming less diverse, and more sys­temic failures are occurring because everybody looksthe same and is holding the same assets. Big firmsnever seem to be as risk taking as their smaller coun­terparts. When two firms merge, the trading floordoes not become twice as large. The trading floorstays about the same size as it was before the twofirms merged. The total risk-taking capability, how­ever, is about half of what it was before. In fact, thesituation gets even worse because two firms do notmerge into one big firm in order to become a hedgefund. Firms merge in order to conduct retail, high­franchise business. Risk taking becomes less impor­tant, even somewhat of an annoyance. Although withconsolidation the firm has more capital and morecapability to take risk, it is less willing to take risk.

Policy IssuesThe markets are changing, and thus, risk managementmust change along with them. But often, changesresulting from reactions to market crises create moreproblems than they solve. Policy issues surroundingtransparency, regulation, and consolidation coulddramatically affect the future of risk management.

Transparency. The members of the LTCMbank consortium (the creditors of LTCM that tookover the firm in September 1998)complained that theywere caught unaware by the huge leverage of thehedge fund. Reacting to the losses and embarrassmentthey faced from the collapse, some of the consortiummembers entered the vanguard for increased trans­parency in the market. They argued that the only wayto know if another LTCM is lurking is by knowingtheir trading clients' positions.

The issue of hedge fund transparency maydeserve a fuller hearing, but opaqueness was not theculprit for LTCM. A simple back-of-the-envelope cal­culation would have been sufficient to demonstrateto the creditors that they were dealing with a veryhighly leveraged hedge fund. The banks-and every­one else in the professional investment community­knew that LTCM's bread and butter trading wasswap spreads and mortgage spreads. Everyone alsoknew that on a typical day, these spreads move byjust a few basis points-a few one-hundredths of apercent. Yet historically, LTCM generated returns forits investors on these trades of 30 percent or more.The only way to get from 5 or 10 basis points to 30 or40 percent is to lever more than 100 to 1.

If the banks were unable to do this simple calcu­lation, it is hard to see how handing over reams oftrading data would have brought them to the sameconclusion. Often in trading and risk management, itis not lack of information that matters; it is lack of per­ceiving and acting on that information. Indeed, look­ing back at the major crises at financial institutions­whether at Barings Securities, Kidder, Peabody &Co., LTCM, or DBS-finding even one case in whichtransparency would have made a difference is hard.The information was there for those who wereresponsible to monitor it. The problem was that theyeither failed to look at the information, failed to askthe right questions, or ignored the answers.

Indeed, if anything, the LTCM crisis teaches usthat trading firms have good reasons for beingopaque. Obviously, broadcasting positions dissipatespotential profit because others try to mirror the posi­tions of successful firms, but it also reduces marketliquidity. If others learn about the positions and takethem on, fewer participants will be in the market readyto take the opposite position. Also, if others know thesize of a position and observe the start of liquidation,they will all stand on the sidelines; no one will wantto take on the position when they think a flood offurther liquidation is about to take place. Transpar­ency will come at the cost of less liquidity, and it is lowliquidity that is at the root of market crisis.

Regulation. Regulation is reactive. It addressesproblems that have been laid bare but does not con­sider the structure that makes sense for the risks thathave yet to occur. And indeed, by creating furtherrules and reporting requirements to react to the ever­increasing set of risks that do become manifest, regu­lation may actually become counterproductive byobscuring the field of view for financial institutions tothe areas of risk that have yet to be identified. At somepoint, the very complexity of the risk managementsystem gets in its own way and actually causes moreproblems than it prevents. We are not at that point yetin the financial markets, but some precedence existsfor this phenomenon in other highly regulated indus­tries, such as airlines and nuclear energy.

The thing to remember is that every new riskmanagement measure and report required by regu­lation is not only one more report that takes limitedresources away from other, less well-defined riskmanagement issues; it is also one more report thatmakes risk managers more complacent in thinkingthey are covering all the bases.

Consolidation. I have already discussed theimplications of consolidation on risk taking. Withevery financial consolidation, the capacity of the mar­ket to take risk is reduced. Large financial supermar-

A Framework for Understanding Market Crisis

kets and conglomerates are created to build franchise,not to enhance risk taking.

Consolidation also increases the risk of the mar­ket, especially the risk of market crisis. The increasein risk occurs because the market becomes less differ­entiated. A greater likelihood exists that everyonewill be in the same markets at the same time and willshare the same portfolios. The investment habitatbecomes less diverse.

The drop in habitat diversity from financial con­solidation looks a lot like the drop in retail diversitythat has occurred as interstate highways and massmedia have put a mall in every town and the samestores in every mall. Whether in food, clothing, orhome furnishings, regional distinctions are disap­pearing. "The maIling of America" is creating a sin­gle, uniform retail habitat.

Coming soon will be "the malling of Wall Street."Broker/ dealers are consolidating into a small set ofinvestment "super stores." On the investor side, moreand more investors are taking advantage of readyaccess to information and markets, but along with thisinformation advantage comes a convergence of viewsamong investors-particularly the retail or individualinvestors-because the information sources are all thesame.

When the Glass-Steagall Act was passed, in alllikelihood Congress did not have in mind diversifyingthe ecosystem of the financial markets. Glass-Steagallcreated a separation between different types of finan­cial institutions in order to protect investors. The sep­aration and resistance to certain types of consolidationis still needed but now for another reason-to main­tain a diverse habitat. The goal of any Glass-Steagall­type reform should be to maintain different types ofrisk takers. It should encourage differentiation amongfinancial market participants so that if one liquiditysupplier is not supplying liquidity in a particularadverse circumstance, another one is, thus helping toprevent or minimize a full-blown crisis.

Some people think of speculative traders as gam­blers; they earn too much money and provide noeconomic value. But to avoid crises, markets musthave liquidity suppliers who react quickly, who takecontrarian positions when doing so seems imprudent,who search out unoccupied habitats and populatethose habitats to provide the diversity that is neces­sary, and who focus on risk taking and risk manage­ment. By having and fostering this differentiated roleof risk taking, market participants will find that criseswill be less frequent and less severe, with less onerousconsequences for risk management systems. Thehedge funds, speculative traders, and market makersprovide this role.

17

Risk Management: Principles and Practices

Question and Answer SessionRichard M. Bookstaber

Question: Could you discussthe u.s. Federal Reserve's role inthe LTCM crisis?

Bookstaber: Other solutionscould probably have been found ifmore time had been available. TheFed could have waited until thingsworked out, but the Fed tookanother course because it per­ceived a time of real financial crisis.These were the major financialmarkets of the world, and ifsomething had not been done, thesituation could have been muchworse. It was already much worsefrom a systemic standpoint thanthe crash of 1987,but from theperspective of most individualinvestors, the crisis was behind thescenes because it dealt with esoter­ic instruments. For the financialmarketplace, however, these werethe primary financial instruments.

The Fed has taken a lot of heatfor its activist role, but in that posi­tion, you have to step up and dowhat you think is right even if youhave to explain afterwards. It is amark of courage and perspicacityon the part of the Fed that it wouldtake the step that was necessary,even if the action was unorthodoxand opened the Fed up to criticism.The alternative wouldhavebeenfarworse. At least we have the luxuryof debating the propriety of theFed's actions and whether therewas some conflict of interest. Iwould rather be debating than deal­ing with the aftermath if nobodyhad protected these markets.

Question: How do investorsprotect themselves from themalling of Wall Street and lack ofdiversification among participants?

Bookstaber: If you are an indi­vidual investor, the malling of

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Wall Street probably does notmatter quite so much because yourpositions are small and you can getout quickly. If you are an institu­tional investor, you have to startlooking at diversification in adifferent dimension. Low-energydiversification is the Markowitzdiversification. High-energydiversification is looking at diver­sifying among net asset classes,among market participants, andamong habitats so that if some­thing happens in one area, it is lesslikely to affect your holdings inother areas. The more that global­ization and the malling of WallStreet occurs, the harder it is to dothat high-energy diversification,because Wall Street goes beyondthe boundaries of Wall Streetor theUnited States. Capital can flowfrom anyplace to anyplace else.

Question: If these crises are theresult of a time disintermediationbetween liquidity suppliers anddemanders, why don't the marketsrecover much faster?

Bookstaber: If you think it tooka long time for recovery-whetherit was the crash of 1987, LTCM, orthe junk bond crisis, which was amultiyear ordeal-that is, unfortu­nately, the nature of systemic risk.Recovery could have been muchslower and more painful than itwas. In a normal market, liquiditydemanders are serviced by liquid­ity suppliers who are in the market,and participation in the market is afunction of price. When a cycle iscreated in which prices do theopposite of what they are sup­posed to do and suppliers disap­pear or become demandersthemselves, that is a wrenchingexperience for all concerned, espe­cially those who have not had such

a previous experience. As is thecase with any experience thatshatters our illusions and causes usto rethink long-held assumptions,recovery comes slowly.

If the suppliers had been thereat the same time as the demanders,October 19, 1987, would have justbeen another day and prices wouldnot have dropped 20 percent. If thesuppliers had been there for LTCMso that when LTCM had that firstmargin call it could have sold at areasonable price and met the mar­gin, then life would have gone on.Neither scenario happened, andrecovery was difficult.

Question: How would youdescribe your view of risk manage­ment?

Bookstaber: I think about themarkets as a scientific enterpriserather than an accounting enter­prise. Many facets of the marketsare accounting oriented, or themathematical equivalent ofaccounting; examples includemodem portfolio theory and thecapital asset pricing model. Theseaccounting-type models areimportant, but we have to lookbeyond the simple relationshipsand resulting output.

During the oil crisis in the mid­1970s, the speed limit was droppedto 55 miles per hour. One firm ranthis information through its mod­els and discovered that auto insur­ers would profit from the reductionin the speed limit. Wehave to learnto make this type of connectionbetween an oil crisis, lower speedlimit, and the decision to buy stockin auto insurance companies.When Chemobyl blew up, a lot ofpeople saw it only as a terribleevent, but somebody saw it as anopportunity to buy wheat futures.

A Framework for Understanding Market Crisis

Making that kind of connection iseasy to do after the fact and doesnot require deep analytical tools,but it does require a scientific oranalytical view of how the world istied together.

Looking at risk managementfrom a scientific perspective isimportant because the risk thatfinally hurts most is the risk that

you do not know about. Refiningour bread and butter measures ofrisk-VAR,stress tests, and similartools-will not bring us muchcloser to uncovering the most crit­ical risks. Granted, they are valu­able tools for measuring well­known risks, and they are capableof assessing the likelihood of some­body losing money because a

known market factor, such as inter­est rates or equity prices, movesprecipitously. But what mattersmost are the risks we do not recog­nize until they occur; after the fact,it is always easy to say, "1shouldhave known that." The challenge isto try to see the risk ahead of time,to imagine the unimaginable.

19

Risk Management and Fiduciary DutiesRobert M. McLaughlin1

PartnerEaton & Van Winkle

Risk management for firms in the investment profession must address the potential forfiduciary violations, especially in derivative-related activities. Analysis of fiduciaryrelationships, laws, duties, and court cases provides guidance for minimizing the risk offiduciary violations.

Examination of theactivities offiduciaries involves,above all, aninquiryintothepropriety ofprofit-making.What isat stake iswhether thecourtshould sanction orstigmatize aparticular actperformed byabusinessmanin a commercial context.2

It is striking to see contemporary courts . . . haulprofessional trustees over the coals for investmentpolicies that few financial economists would findexceptional.'

F iduciary law is a highly compartmentalized, com­plex field with as many different branches of law

as there are types of institutions, investors, and invest­ment managers. Worse yet, a distinctive feature offiduciary law-especially in its application toderivatives-is its often elusive and unpredictablemoral underpinning. When large unexpected lossesoccur, it is all but inevitable that charges of fiduciarywrongs will follow; indeed, large losses are often con­strued as invitations to litigation and regulatoryenforcement actions. But capital markets depend onrisk taking, and when risky economic decisions resultin judicial and regulatory responses that are based onattacks against the decision makers for supposed fidu­ciary violations, the results can be highly destructive.Penalizing business and investment decisions thathappen to tum out badly risks stifling economic activ­ity (in addition to being unfair) and thus has the poten­tial for doing more harm than good. It also causesdoctrinal confusion and, of significant importance tofiduciaries and their advisors, legal uncertainty,

IThis presentation is adapted from Robert M. McLaughlin, Over­the-Counter Derivative Products: A Guide to Businessand Legal RiskManagementand Documentation (New York: McGraw-Hill, 1999).2EmestJ.Weinrib, "The Fiduciary Obligation," Universitya/TorontoLawJournal, vol. 25 (1975):1~2.

3 Jeffrey N. Gordon, "The Puzzling Persistence of the ConstrainedPrudent Man Rule," N.Y.U. Law Review(April 1987):52, 66.

20

An important task, then, is to develop an analyt­ical approach that reduces the legal uncertainty sur­rounding fiduciary conduct and, by so doing,provides practical guidance to (1) fiduciaries, (2)those who wish to benefit from fiduciary law's pro­tections, and (3) those who are charged with respon­sibility for administering fiduciary law. In thispresentation, I attempt to develop such an approachand thereby offer practical guidance on minimizingthe risk of potential fiduciary violations and the riskthat the protections afforded by fiduciary law willinadvertently be forfeited. The presentation does soby focusing on• the structure of fiduciary relationships,• the function of fiduciary law, which follows di­

rectly from that structure-namely, the law pro­tects benefited parties from the risks that arisefrom their "structural dependence" on their fidu­ciaries,

• important differences in the way fiduciary andcontract law treat written contracts, which canhave a direct impact on risk management prac­tices, and

• lessons from the limited derivative-related fidu­ciary duty case law and from cases on other mat­ters relevant to the supervision-internal andexternal---of derivative activities.

Note that the presentation will not cover"controls" assuch, although the discussion will have definite con­trolimplications. Nor will it focus on the fiduciary lawof any particular jurisdiction or regulatory regime.

Fiduciary RelationshipsA threshold point to be made in any discussion offiduciary relationships, and one often overlooked, is

© 1999 Robert M. McLaughlin

that whether a relationship is or is not legally afiduciary relationship is a question ultimately decidedby courts-and not always according to the parties'intentions. In classifying relationships, courts givegreat weight to those intentions, especially as set forthin written agreements and evidenced by other factsand circumstances. Courts ordinarily honor, for exam­ple, both express disclaimers and express assump­tions of fiduciary duties. Yet although the parties'intentions and contractual provisions are important,they are not controlling. Courts readily look beyondthe "four comers" of a contract to examine such exter­nal factors as equity, public policy, and state-imposedlimitations on the parties' capacity and freedom tostructure their dealings privately. External factors canreadily lead to rulings that defeat the parties' inten­tions by unexpectedly imposing fiduciary obligationsor, in contrast, by rendering the protections of fidu­ciary law unavailable.

Because of courts' willingness to examine externalfactors in classifying relationships, it can be dangerousfor parties to rely solely on the language of their writ­ten agreements to determine their legal rights andobligations. The inconclusive nature of written agree­ments can make it difficult to decide when someonehas incurred fiduciary duties and, if so, what the spe­cific content of those duties might be. A functionalanalysis of fiduciary relationships, on the other hand,helps to reduce that uncertainty and minimize sur­prises. It does so by focusing on six common elementsshared by all fiduciary relationships.

Relationship for Provision of Services. Thefirst element of a fiduciary relationship is that it musthave been established for the provision of services byone party (the fiduciary) to another party (which, forlack of a better term, I will follow Frankel and call the"entrustor") with respect to property or assets.Frankel coined the term "entrustor" to connote thetwo "unifying features of all fiduciary relations.,,4First, the root "trust" identifies the substitution func­tion that a fiduciary performs, standing in the entrus­tor's place as to entrusted matters. Second, "entrust"suggests a delegation of powers to the fiduciary forperforming the contemplated services. "Entrustor,"although an imperfect term, is more descriptive andless confusing than the available alternatives. Themost common, of course, is "beneficiary," but thatseems an odd term for describing such diverse per­sons as general partners, joint venturers, patients ofphysicians or psychiatrists, clients of lawyers, unionmembers, stockholders, and at times, evenbondhold­ers and institutional lenders-all of whom enjoysome fiduciary law protections.

4Tamar Frankel, "Fiduciary Law," California Law Review (May1983):800, Note 17.

Risk Management and Fiduciary Duties

The principal concern here is with two importantcategories of fiduciary services: the management ofinvestment portfolios and the management of large­scale, indivisible business enterprises that are fundedwith the pooled capital of numerous security holderswho, in tum, share ownership and risks.

Delegated, Discretionary Power. The secondelement is that a fiduciary receives delegated, discre­tionary power over some property of the entrustorand it receives that power to enable it to perform thecontemplated services. Potential reasons for the del­egation are, of course, numerous. An entrustor might,for example, simply prefernot to perform the relevantservices for itself. Or perhaps, the entrustor lacks thetime, expertise, or facilities to perform those servicesefficiently. In any event, as discussed below, if thefiduciary is to be able to perform those services prop­erly, the power delegated to it must be discretionary.

Moreover, in exercising that power, the fiduciaryacts for the benefit of the entrustor as its substitute or"alter ego." Of critical legal importance is that thedelegation is not for the fiduciary's benefit but solelyto facilitate the performance of the particular servicesfor the entrustor. Thus, the fiduciary has no indepen­dent right to use or assume the property or powers forits own benefit; it has no inherent right to share in anyinvestment gain or corporate profit. Any indepen­dent right to use the delegated power or property forthe fiduciary's benefit must be expressly stated in acontract or otherwise unambiguously provided for.

Prohibitive Costs. The third defining elementof fiduciary relationships is that the exact actions tobe taken by the fiduciary in discharging its responsi­bilities are subject to so much uncertainty and somany variables that prespecifying those actionswould be futile or impractical. Futility arises whenany effort to precisely predetermine the fiduciary'sconduct would deprive the fiduciary of the ability toexercise its expertise meaningfully; impracticalityoccurs when the costs-in terms of time and money­of prespecifying are prohibitive.

Portfolio investing and corporate managementfrequently involve so much risk and uncertainty thatit is impossible to dictate in advance the fiduciary'sspecific behavior without undermining the purposeand benefits of the relationship. Specifying, forexample, counterparty credit concentrations andcountry exposure limits is important and often suf­ficiently measurable to permit objective verificationof the fiduciary's performance. But trying meaning­fully to specify, for example, how the fiduciaryshould react to proposed deal terms prior to any offerbeing made or how the fiduciary ought to respond

21

Risk Management: Principles and Practices

to specific changes in market conditions withoutknowing in advance what those changes might be atthe time is pointless. The difficulties of prespecifyingthe fiduciary's conduct are exacerbated by the factthat fiduciaries, particularly portfolio managers andexecutives of financial and industrial companies, arehired not because they are especially honest or trust­worthy but precisely because of their knowledge,expertise, and judgment. In restricting the exerciseof discretion, an entrustor limits its fiduciary's abilityto apply that knowledge and expertise and its inde­pendent judgment.

"Structural Dependence": Risk of Negligenceor Misappropriation. By delegating discretionarypower over their property, entrustors becomeexposed to the risk that their fiduciaries may exercisethat power carelessly or for their own benefit. Herelies the central problem of all fiduciary relationships:Namely, the delegation of discretionary power to thefiduciary to enable it to perform the contemplatedservices renders the entrustor dependent on its fidu­ciary for the performance of those services and for theprotection of the entrusted property. Furthermore, asdiscussed below, the entrustor's structural depen­dence on its fiduciary cannot be satisfactorily allevi­ated through direct control and monitoring of thefiduciary's performance.

Inadequacy of Direct Control and Monitor­ing. The fifth element of a fiduciary relationship isthat direct control of the fiduciary by the entrustor isso impractical, or costly and inefficient, that it under­mines the purpose of the relationship. For example,once entrustors have hired expert money managersor corporate executives, they seldom want, or havethe time and ability, to consider, direct, and reviewevery investment decision or business judgment thatneeds to be made. And when numerous investorspool their capital, potentially serious and costly "col­lective action" problems arise that hinder any effortto exercise direct control.

Consider the traditional trust relationship, forexample. Assume that many beneficiaries wouldbenefit from a lawsuit brought to compel the trusteeto take a given course of action. But which beneficiaryis going to fund the lawsuit, given that the benefi­ciary's costs and expenses are generally not reim­bursable from the trust's assets and that the otherbeneficiaries will have no legal obligation to share inthem? Or consider the fate of a public stockholderwho wants to launch a potentially costly proxy battleagainst an allegedly dishonest management team.Even though all other stockholders could benefit ifthe allegations are correct and the stockholder issuccessful, those others will have no direct legal obli­gation to help fund the proxy contest.

22

Monitoring is also limited in its effectiveness.Among other things, the effectiveness of any moni­toring effort will depend on the quality and frequencyof reporting. Unfortunately, the reporting is often tooinfrequent. Moreover, the information reported istypically prepared either by, or under the supervisionof, the fiduciary. Monitoring, as a form of after-the­fact protection, is also flawed in a more unsettlingway. In particular, reports about the results of a man­ager's decisions may say little about the quality ofthose decisions given the circumstances under whichthey were made. Good decisions can have bad results,and results can be ambiguous or otherwise difficultto evaluate. A lot of smart, diligent people have lostmoney following perfectly reasonable investmentstrategies. In short, outcomes are inconclusive.

Alternative Controls. Finally, courts will usu­ally find fiduciary relationships and, therefore,impose fiduciary obligations only if they are con­vinced that no effective alternative controls, market­based or otherwise, are present to limit the entrus­tors' dangers of delegation. The most common alter­native control is the availability of a trading marketthat enables an investor to dispose of investments,thereby terminating any potential fiduciary relation­ship with the issuer's management. Public stockhold­ers, for example, who hold highly liquid shares cansell their stock if they disapprove of management'sactions. Corporate directors and officers usually havea powerful self-interest in maintaining high stockvalues and ought to be reluctant to take actions thatare contrary to stockholders' interests. Reliance onmarket forces alone is of limited use because it worksonly with securities trading in liquid markets andunder favorable market conditions. Entrustors areordinarily unable to "vote" against management,except at great cost, by selling their securities whenthe issuer's securities are thinly traded.

Fiduciary LawA functional approach to fiduciary relationships illu­minates the major reasons why the law is so con­cerned with the protection of entrustors. Thisapproach begins by separating the fiduciary's con­templated services from the entrusted property thatenables the fiduciary to perform those services.

"Extraordinary" Risk of Loss. A risk arises inany fiduciary investment relationship from the factthat the fiduciary's services, even if valuable, arelikely to be less valuable than the invested capital.By delegating power over its property to a fiduciary,and by parting with that power, an entrustorexposes itself to a risk of loss that may have nothing

to do with the investment itself; losses may occursolely as a result of the fiduciary's carelessness ormisappropriation. Because its capital is at risk, theentrustor's potential loss can be extraordinary anddisproportionate to the benefits to be derived fromthe relationship-such loss may greatly exceed thevalue of the fiduciary's services.

Furthermore, abuse by a fiduciary that leads toinvestment loss can be exceptionally difficult todetect so long as the fiduciary maintains legitimateand exclusive possession of the entrusted property."Fiduciary risk" is unlike market or investment risk,from which one might reasonably expect to incurlosses from time to time as perhaps an unavoidablecost of generating profits; entrustors do not enter intobusiness or investment relationships expecting theirfiduciaries occasionally to misappropriate funds orinvest carelessly. An entrustor may, then, be caughtoff guard by its fiduciary's abuse and with little real­istic ability to protect itself.

Function of, and Limitations on, FiduciaryLaw. The function of fiduciary law is to protectentrustors from the disproportionate, extraordinaryrisks inherent in the structure of fiduciary relation­ships. The law endeavors to protect the entrustorfrom the risk of loss resulting from a fiduciary'spotential carelessness with, or misappropriation of-often likened to embezzlement-entrusted prop­erty. Properly understood, fiduciary law is neither aguarantee that a portfolio or business will never incursignificant losses nor an assurance that a portfolio orbusiness will perform as expected. The law is sophis­ticated enough to recognize that even sound portfolioinvestment principles and business strategies canproduce unexpected losses. Fiduciary law's basicconcern is rooted in the strong public policy of pro­moting socially desirable relationships by affordingentrustors legal protections that might otherwise beunavailable, too costly, or impractical to obtain.

One of the most compelling public policy ration­ales for fiduciary law is the phenomenon of specializa­tion: Specialization increases within society the sum ofavailable expert services, which is essential to modemeconomies because it enhances economic efficiency.

Exclusive Benefit Principle. Fiduciary law'sone-sided concern, embodied in its so-called exclusivebenefit principle, is to protect the entrustor by impos­ing on the fiduciary mandatory legal obligations­specifically, the duties of loyalty (which essentiallymeans no self-dealing with entrusted property) andcare. Fiduciary law is not concerned with how a rela­tionship is established or with the relative sophistica­tion of the parties but only with the structure of therelationship. Although structure may be evidenced by

RiskManagement and Fiduciary Duties

contractual terms, the law does not require anagreement-written or otherwise-in order to find afiduciary relationship. Rather, courts can impose fidu­ciary duties as a matter of law and even contrary tothe parties' intentions if they find the requisite delega­tion of power over an entrustor's property under cir­cumstances that expose the entrustor to extraordinaryrisks of its fiduciary's misconduct. For tha t reason, onemay be surprised to learn that courts can readily findfiduciary violations by persons who never intendedto assume fiduciary obligations.

Even a fiduciary's right of compensation and ofreimbursement of expenses is designed to protect theentrustor. Without compensation, few people wouldbe willing to act as fiduciaries in most commercialrelationships, especially those that are viewed as eco­nomically risky. Similarly, the fiduciary's right ofreimbursement is designed to ensure that the fidu­ciary takes all necessary and appropriate steps toperform its services properly. If, for example, imme­diate action is essential-maybe to preserve capitalor take advantage of a fleeting investment opportu­nity-it is likely to be in the entrustor's interest thatthe fiduciary not forgo that action simply because ofconcern over who will bear the expense.

Relationship Structure. When courts analyze arelationship's structure to determine whether it givesrise to fiduciary duties, they begin with and lookcarefully at the express and implied terms of the par­ties' agreement. One can often infer a relationship'sstructure from its contractual terms. Nevertheless, aspreviously noted, the law does not require an expressor even an implied agreement by the fiduciary toassume any obligations that are fiduciary in character.

As discussed earlier, a delegation is both a grant(to the fiduciary) and a ceding (by the entrustor) ofpower that renders the entrustor dependent on thefiduciary as to the entrusted property. Express anddetailed restrictions and controls on the fiduciarywould be either unrealistic or so costly that theywould defeat the purpose of the relationship. Never­theless, the delegation of power and inability of theentrustor to monitor and directly control the use ofthat power expose the entrustor to real risk.

Of interest in derivative cases is that the depen­dency that triggers fiduciary duties can arise evenwith highly sophisticated entrustors who in mostother business and investment contexts would not belikely to be the kinds of parties thatthe law is solicitousof protecting. Most of the major derivative litigationto date has involved otherwise sophisticated institu­tions, such as Procter & Gamble and Gibson Greetings.

Moral Stigma. The entrustor's structural depen­dence has long been the source of the law's moral

23

Risk Management: Principles and Practices

indignation with violations of fiduciary duties. Injustifying the imposition of onerous penalties on fidu­ciaries, modem courts seem to reflexively reciteJudge Cardozo's famous 1928dictum that a fiduciaryis "held to something stricter than the morals of themarket place. Not honesty alone, but the punctilio ofan honor the most sensitive, is then the standard ofbehavior.rf A finding of a violation implies dishon­orable or irresponsible conduct, and a serious moralstigma generally attaches to fiduciaries who arefound to have violated their fiduciary duties. In addi­tion to potentially resulting in monetary and otherdamages, the stigma of fiduciary violations can causeserious reputational harm.

Stigmatizing complex financial decisions thathappen to tum out badly is deeply disturbing, partic­ularly so with derivatives, where one should expecteven perfectly designed and executed risk manage­ment programs to incur derivative losses from time totime. Hedging programs that use derivatives ofteninvolve joint transactions in which gains on deriva­tives offset losses on underlying assets, and vice versa.Logically, in a perfectly designed and implementedhedging program, either the derivative or the hedgedasset is expected to incur a loss as market conditionschange. Punishing fiduciaries simply because thelosses incurred in a sound hedging program hap­pened to fall on the derivative side of the joint trans­action strikes one as arbitrary and unfair.

Even the case Cardozo wrote about betrays thetensions that can arise in judicial attempts to stigma­tize complex business decisions. The case involved areal estate venture in which the parties' agreementssimply did not contemplate, expressly or otherwise,the events that led to their dispute. Suffice it to saythat one party, a property manager, took advantageof a business opportunity presented to him duringthe term of the venture without informing his coven­turer of that opportunity or affording him a chanceto participate in it. Although the manager may haveadopted an aggressive business approach, the claimthat the plaintiff was in any meaningful way harmedby or structurally dependent on the manager is dubi­ous. And it is unlikely that either party would haveexpected during the course of their relationship thatthe relationship was fiduciary in nature. The decisionwas rendered by a sharply divided court; three ofseven judges dissented vehemently, arguing compel­lingly that nothing in the law or facts before themwarranted the imposition of fiduciary duties.

5Meinhard v. Salmon, 249 N.Y. 4S8 (1928):464. Emphasis added byauthor.

24

Fiduciary Law versus Contract LawA meaningful understanding of the essential differ­ences between fiduciary and contract law­particularly the different weights they give writtenagreements-is vital to any effort to minimize risksof fiduciary violations.

Fiduciary Law. The principal objective of fidu­ciary law in the economy is to foster beneficial busi­ness and investment relationships by protectingentrustors' property rights. Fiduciary law, therefore,imposes substantial restrictions on fiduciaries' free­dom to "contract around" or "out of" their duties ofcare and loyalty. Fiduciary law is particularly aggres­sive in protecting the interests of passive investorsfrom fiduciaries' opportunistic behavior, especiallywhen those investors are information disadvantaged(i.e., are dependent on their fiduciaries to providerelevant information about their investments).

At a minimum, the law subjects any attemptmade by fiduciaries to limit the nature and scope oftheir fiduciary duties to rigorous procedural precon­ditions. Before giving effect to waivers of fiduciaryduties, courts typically demand convincing evidencethat waivers, for example, were granted only afterfull disclosure to the entrustor of all material facts;they also require evidentiary showings that the waiv­ers were knowingly made by entrustors who pos­sessed a realistic ability to refuse to waive.

Contract Law. Contract law, on the other hand,stresses the values of personal freedom and autonomy. Itassumes that contracting parties are fully capable oflooking out for and protecting their own best interests.Thus, contract law places great weight on the terms ofthe parties' agreement, which the parties are pre­sumed to have freely chosen for themselves. Absentevidence to the contrary, the parties are assumed tohave acted in good faith, and each party acts andexpects the other to act in his or her own best interest.Under a traditional contract law analysis, the state'srole is limited to merely ensuring completion of thecontract; thus, the only role that a court should play ina contract dispute is to determine and give effect to theparties' actual intentions, based on the express terms oftheir agreement and any other terms that are impliedfrom the nature of the relationship or transaction.

Contract law traditionally does not take theexpansive approach to interpreting duties that fidu­ciary law does. Some commentators and at least oneprominent federal court argue that the traditional,narrow approach to interpreting contracts should alsobe used to interpret fiduciary duties. In particular, theU.S. Court of Appeals for the Seventh Circuit hasadvocated strenuously for a contractual approach to

fiduciary duties. It has, in effect, asserted that fidu­ciary duties are merely the equivalent of implied con­tract terms-that they are in essence gap fillers thatmerely complete the missing details of an agreementthat the parties may not have taken the time them­selves to supply. In the court's words: "The fiduciaryduty is an off-the-rack guess about what partieswould agree to if they dickered about the subjectexplicitly.r'''

Market-Based Protections. Whether under acontract law or fiduciary law analysis, courts gener­ally recognize that alternative market mechanisms(e.g., the presence of a liquid secondary market thatenables stockholders to exit their investment relation­ships with minimal transaction costs) may reduceinvestors' need for expansive legal protections, espe­cially those afforded by traditional fiduciary law.Courts, such as the Seventh Circuit mentioned earlierand Delaware state courts, emphasize that moderneconomies depend on important and beneficial busi­ness and investment relationships. Accordingly,overdeterrence of managerial risk taking threatensthose relationships, and punishing managers for eco­nomic decisions that are morally inconclusive orambiguous could kill risk taking by increasing man­agers' natural risk aversion. Such punishment couldalso deter qualified candidates from becoming invest­ment managers or corporate officers and directors.

Moreover, courts have voiced recent concernsover the disproportionality of imposing liability forcorporate losses on officers and directors. In thewords of a Delaware court:

Given the scale of operation of modem publiccorporations, this stupefying disjunction betweenrisk and reward for corporate directors threatensundesirable effects.... The law protects share­holder investment interests against the uneco­nomic consequences that the presence of . . .second-guessing would have on director actionand shareholder wealth?

Trust Law versus Corporate LawTrust law and corporate law also differ in their treat­ment of fiduciary relationships. The differences canadd a layer of complexity-beyond that encounteredin the tension between fiduciary and contract law­to any examination of the duties business and invest­ment managers might owe to their investors.

6Jordan v. Duff and Phelps, Inc., 815 F.2d 429 (7th Cir. 1987) (Easter­brook, J.),cert. dismissed, 485 u.s. 901 (1988).

7Gagliardi v.Trifoods International, lnc., 683 A.2d 1049,1052 (Del. Ch.July 19, 1996).

RiskManagement and Fiduciary Duties

Trust Law. Traditional trust law imposes thestrongest duties on fiduciaries and encourages thehighest degree of risk aversion because the benefi­ciary's structural dependence is at its greatest in atrust relationship. As mentioned earlier, beneficiariesusually have little meaningful ability to remove trust­ees, and they are usually not involved in trusteeselection. Moreover, trust beneficiaries have littlepractical ability to exit the relationship without suf­fering substantial losses. Consider the options avail­able to those who become trust beneficiaries throughinheritance: Few have any meaningful ability tobreak their trusts and acquire direct control of thetrust assets. Indeed, the very purpose of the trust isoften to prevent the beneficiary from gaining suchdirect control.

Furthermore, when a trust has multiple benefi­ciaries, those beneficiaries usually face substantialcollective-action problems should they ever wish toattack the trustee's decisions. As noted earlier, suchbeneficiaries are usually not entitled to reimburse­ment from the trust assets for costs and expensesincurred in attempting to influence the trustee'sactions.

Historical approach. Trust law throughout theUnited States used to be-and in a diminishing num­ber of states still is-severely, almost arbitrarily, hos­tile toward most financial activities involving eitherinvestment risk or speculation. Under the old view,which typically goes under the heading of the Pru­dent Man Rule, investment risk is seen as the one­sided chance of loss, or what many today call"down­side risk." Until as late as the 1950s, trust law evenlabeled investments in common stock as automati­cally "speculative" and, therefore, impermissible. Infact, the Prudent Man Rule holds that many catego­ries of investments are "imprudent per se. Accord­ingly, the exercise of care, skill, and caution would beno defense [to liability] if the property acquired orretained by a trustee or the strategy pursued by atrust was characterized as imperrnissible.rf That is,until relatively recently, trust law has been openlyhostile toward most financial activities that involveany kind of investment risk.

Until recently, the dominant philosophy under­lying trust law was deeply antagonistic toward allow­ing trustees to offset portfolio gains and losses. It alsorevealed a near absolute emphasis on ensuring thateach individual investment within a portfolio wasdesigned to minimize risk of loss on that investment.

8Restatement of the Law Third, Trusts, Prudent Investor Rule, asadopted and promulgated by the American Law Institute, Wash­ington, D.C.. May 18, 1999 (American Law Institute Publishers.1992):3--4.

25

Risk Management: Principles and Practices

Even the law's express diversification require­ment had as its sole purpose "minimizing the risk oflarge losses." That form of diversification require­ment, which also continues in a diminishing numberof states, mandated diversification solely for the pur­pose of minimizing the risk of loss. There was noevident awareness that through diversification, trust­ees might improve the economic"efficiency" of theirportfolios. Ultimately, the restrictions placed ontrustees rendered trust law, albeit unintentionally,also antagonistic toward beneficiaries because thebeneficiaries bore the ultimate costs-in the form ofsuboptimal portfolios and unnecessary costs andexpenses-of their trustees' inability to rely on mod­ern portfolio theory and investment techniques.

Note that it is prudent today for any trustee orother fiduciary who manages risky investments,whether or not including derivatives, to determinewhether the law that governs the investment relation­ship is the old Prudent Man Rule. If so, certain cate­gories of instruments, such as derivatives, may bedeemed imprudent per se. In that case, even the exer­cise of care, skill, and caution will afford no defenseagainst losses if either an investment made or strategypursued is characterized as impermissible.

II Recent approach. By 1990, a dramatic shift hadtaken place in the law of many jurisdictions. Trustinvestment law, through a new Prudent InvestorRule, began explicitly to recognize and accept mod­ern investment principles. In particular, it now viewsrisk in the modern sense of two-sided uncertainty ofoutcomes, comprising both "upside" and "down­side" exposures. The new law incorporates modernportfolio theory into its diversification requirement,and it treats no investment strategy or technique,including those that use derivatives, as automaticallyprohibited.

The reason for the shift is a growing recognitionthat "prudent risk management is concerned withmore than ... the loss of dollar value. It takes accountof all hazards that may follow from inflation, volatil­ity of price and yield, lack of liquidity, and the like."9The new Prudent Investor Rule expressly refrainsfrom classifying any investment or technique asimprudent in the abstract. Instead, it attempts toprovide the law with a measure of generality andflexibility and thus attempts to free trustees fromrigid and arbitrary investment constraints. In juris­dictions that have adopted the Prudent Investor Rule,the prudence of a trustee's conduct will be analyzedbased on a more informed assessment of all relevantfacts and circumstances.

9Id.,at General Comment e.

26

Some commentators have observed that the newrule "liberates" sophisticated trustees by expresslysanctioning the use of popular investment techniquesand instruments and eliminating per se, or auto­matic, liability. In fact, the new rule makes success­fully attacking a trustee's conduct more difficult thanunder the old rule. Given the new rule's focus onoverall portfolio strategy and the complexity of anyassessment of a trustee's performance, courts shouldbe more reluctant under the new rule to conclude thata trustee has acted imprudently.

One important lesson emerging from the newPrudent Investor Rule is that in assessing the pru­dence of a trustee's conduct, courts must now as apractical matter focus more closely on process thanresults. Central factors that are likely to be consideredin most litigation over fiduciaries' investment deci­sions are the manner in which the fiduciary has doc­umented its activities and whether the fiduciary candemonstrate its conformity to agreed-on investmentguidelines. Compliance with fiduciary standards isnow to be

judged ... not with the benefit of hindsight or bytaking account of developments that occurredafter the time of a decision to make, retain, or sellan investment. The question of whether a breachof trust has occurred turns on the prudence of thetrustee's conduct, not on the eventual results ofinvestment decisions.l''The new Prudent Investor Rule clarifies that in

delegating investment authority, a trustee must exer­cise care, skill, and caution in (1) selecting a suitabledelegee, (2) establishing the scope and terms of thedelegation, (3) periodically reviewing the delegee'scompliance with the scope of the delegation, and (4)controlling the costs of the delegation.

ERISA, the U.S. federal Employee RetirementIncome Security Act governing the trustees of U.S.corporate pension funds, likewise accommodatesderivative activities, at least in its interpretationby theU.S.Department of Labor. The DOL wrote in 1996 that"Investments in derivatives are subject to the fidu­ciary responsibility rules in the same manner as areany other plan investments.r"!

Corporate Law. For several reasons, corporatelaw's fiduciary duties are more lenient than thoseimposed by trust investment law, but the most impor­tant reason is that stockholders, at least in public

lOId., at General Comment b.

llLetter dated March 21, 1996, from Olena Berg, U.S. Departmentof Labor, addressed to Hon. Eugene A. Ludwig, Comptroller of theCurrency; see also Lynch v. J.P. Stevens& Co., Inc.,758 ESupp. 976,1013 (D.N.J. 1991). Court observed, in dicta, that nothing in theallegations before it suggested that an investment of plan assets infutures and options was unlawful.

companies, are usually far less structurally depen­dent on their fiduciaries than are trust beneficiaries.Stockholders of most public companies can usuallysell their securities and exit their relationship rela­tively easily, and they enjoy voting rights within thecorporation. They can also seek judicial dissolution ofthe corporations. Moreover, stockholders usuallyenter into their corporate investment relationshipsvoluntarily. Finally, as noted earlier, minimizing the"stupefying disjunction between risk and reward" isa judicially recognized countervailing policy arguingagainst the imposition of strict duties on officers anddirectors.

Consequently, courts have developed the so­called Business Judgment Rule-a rebuttable pre­sumption that in making a business decision man­agement "acted on an informed basis, in good faith,and in the honest belief that the decision was in thebest interest of the company and its shareholders.rl­When successfully invoked, the rule provides officersand directors with a near absolute shield againstliability. Because of the rule's protections, officersand directors are rarely held liable (absent evidenceof self-dealing or conflict of interests) for breaches ofthe duty of care.

Most recent discussions and judicial analyses ofthe Business Judgment Rule, however, offer confus­ing guidance in understanding how the rule wouldlikely be applied in derivative contexts. The bulk ofrecent corporate fiduciary duty litigation has arisen inthe context of heated takeover battles in which strongarguments are typically made that management­particularly in rejecting takeover proposals-actedout of its own self-interest (i.e., out of a desire toperpetuate itself in office) rather than the interests ofthe company and its stockholders. Decisions made bymanagement out of self-interest are not protected bythe Business Judgment Rule. The reason that mosttakeover precedent cases are of limited use here is thatderivative cases seem less likely than takeover battlesto raise questions of managerial self-interest.

Fiduciary DutiesUltimately, courts decide the presence and extent ofany fiduciary duties, typically based either directly orindirectly on state law. No overarching federal fidu­ciary law exists. The u.s. Securities and ExchangeCommission (SEC) has attempted, in effect, to createsuch a law, but the U.S.Supreme Court and a numberof federal circuit courts have repeatedly refused toallow the SEC's view to prevail. (Nevertheless, theSEC does rely on a number of fiduciary issues andfiduciary theories to support the enforcement actions

12Aronson v. Lewis, 473 A.2d 805, 812 (Del. Supr. 1984).

Risk Management and Fiduciary Duties

it brings involving alleged violations of federal secu­rities laws.) In addition, although ERISAdoes imposefiduciary duties on trustees of corporate pensionfunds, the principles applicable to those trustees areprimarily those derived from state trust investmentlaw in general.13

Under state trust law, the mere invocation of afiduciary duty in a contract is insufficient (althoughit helps) to give rise to fiduciary duties if the relation­ship fails to display the requisite structural depen­dence; likewise, an express disclaimer is insufficientto avoid the establishment of fiduciary duties if thatdependence exists. Courts generally (an importantexception appears to be the U'S. Court of Appeals forthe Seventh Circuit) follow the approach of NewYork's highest court, which has stated that "Merewords will not blind us to realities." Because variousapproaches to both disclaimers and assumptions offiduciary duties have been advocated by some indus­try groups, examining briefly a couple of prominentexamples may be useful.

II Assumption example. Consider Risk Standard1:Acknowledgment of Fiduciary Responsibility, con­tained in the Risk Standards for Institutional InvestmentManagers andInstitutional Investors, published in 1996and prepared by a working group of 11 individualsfrom the institutional investment community underthe technical guidance of Capital Market Risk Advi­sors. The Risk Standards offer guidelines that institu­tional investors and investment managers may use intheir own risk management activities. Risk Standard1 asserts that "Fiduciary responsibilities should bedefined in writing and acknowledged in writing bythe parties responsible."

As discussed earlier, most courts would likelygive effect to an express and detailed writtenacknowl­edgment of fiduciary duties, such as those suggestedin the Risk Standards. Nevertheless, that acknowledg­ment should not end one's analysis: One should notethat a court may, depending on the structure of arelationship and any relevant external factors (such asequity or public policy), disagree with the parties'definitions of those fiduciary responsibilities.

Perhaps more important is that the mere absenceof an express acknowledgment of fiduciary duties,such as that suggested in Risk Standard 1, should notbe interpreted as conclusive proof that a manager has

13See,for example, First National Bankof Chicago v. A.M. Castel &Company Employee Trust,1999U'S, App. LEXIS11891(7th Cir., June9, 1999): Where trustee was an ERISA fiduciary, the court foundthat general trust investment law principles applied "rather thananything special to either the regulation of national banks or toERISA." But, cf Rice v. Rochester Laborers' Annuity Fund, 888 ESupp. 494 (WO.N.Y. 1995):The fiduciary duties established underERISA are a more stringent version of the Prudent Person Rulethan under the state common law of trusts.

27

Risk Management: Principles and Practices

not assumed any fiduciary duties: Courts haverepeatedly demonstrated that parties do not need awritten acknowledgment to have entered into a fidu­ciary relationship; courts readily find fiduciary rela­tionships and impose fiduciary duties even withouta written acknowledgment when a relationship dis­plays the requisite structural dependence.

III Disclaimer example. In contrast, the Interna­tional Swaps and Derivatives Association (ISDA) haspublished a suggested standard form of nonrelianceprovision, entitled Representation Regarding Rela­tionships between Parties, which the parties to anISDA Master Agreement may include as an amend­ment to their agreement. Clause (c) of that provision,entitled Status of the Parties, contemplates that eachparty will acknowledge and represent that "the otherparty is not acting as a fiduciary for or an advisor toit." Thus, this provision acts as an express disclaimerof any fiduciary relationship or duties.

The most important question confronting manyparties who incorporate the ISDA disclaimer iswhether it will be judicially upheld, and most courtswould seem likely to uphold it. Nevertheless, thosewho wish to disclaim fiduciary relationships by meansof such a waiver are well-advised to make certain thatthe structure of the relationship does not suggest thatthe other party is structurally dependent on it. Other­wise, again, a court could easily ignore the waiver andimpose fiduciary duties. A subsidiary question iswhether the lack of the disclaimer might be deemed toconstitute evidence that the parties to an ISDA MasterAgreement have entered into a fiduciary relationship.That conclusion is doubtful, especially under NewYork law, where courts are loath to find fiduciaryduties among parties to business relationships.

Lessons from Case LawTwo fairly recent cases should prove especiallyrevealing for anyone attempting to assess fiduciaryduties in the context of derivative activities. Amongother things, the cases suggest several key risk man­agement principles applicable to derivatives thatfiduciaries and their legal advisors should consider.The first case, Brane v. Roth,14 is an Indiana case inwhich a federal trial court held directors liable forbreaching fiduciary duties of care in connection witha failed futures hedging program. The second, Care­mark,15 demonstrates that to invoke the shield of theBusiness Judgment Rule, corporate officers anddirectors must first make a business decision; it alsocasts some doubt over whether a board's perfor-

14590 N.E.2d 587 (Ind. App., 1st Dist., 1992).

15In re Caremark International Inc. Derivative Litigation, No. 13670(DeL Ch., Sept. 25, 1996).

28

mance of its "oversight" role, absent an identifiabledecision, is enough to invoke the rule.

Brane v. Roth. Ironically, this is the derivative­related case that seems to have caused the greatestalarm among commentators, even though itproperlyshould have remained fairly obscure. The caseresulted from a successful action brought by stock­holders of a rural grain elevator cooperative againstthe co-op's directors for losses the co-op suffered onits grain sales, losses that could have been preventedthrough adequate hedging. The directors had, in fact,authorized the use of futures to hedge the co-op'sgrain price exposure. Nevertheless, the co-op failedto hedge; virtually 95-98 percent of its exposuresremained unhedged long after the hedging programhad been authorized.

Although several commentators argue that Branev. Roth is an anomalous case standing for the propo­sition that directors at times have a general"duty tohedge," the case stands for no such thing. It is simplya case in which a court reiterated the longstandingprecept that the Business Judgment Rule does notprotect directors from liability for decisions made onan uninformed basis. (The Brane directors were foundnot to have bothered to learn the "fundamentals" ofhedging with futures and not to have actively super­vised the actual hedging that was done.) That is, thedecision to hedge must be made on an informed basis,and once a decision to hedge has been made, directorshave a duty to supervise the hedging program. Thecourt said that the directors' lack of understanding ofhedging rendered them fundamentally unable to relyon the Business Judgment Rule. And for corporatefiduciaries, the inability to rely on the Business Judg­ment Rule is usually fatal, because in the vast majorityof cases, those officers and directors who are unableto rely on it are held liable.

Caremark. Although not a financial derivativecase, Caremark is important because it involved areview of director oversight responsibilities in cir­cumstances that do not necessarily call for actions ordecisions, circumstances that might easily be foundin many derivative cases. The facts in Caremark pre­sented questions as to whether the directors failed tosatisfy their so-called duty of attention and whetherthat duty is somehow legally distinct from the ordi­nary duty of care. Violations of federal law hadoccurred deep within the organization, and the plain­tiffs claimed that the directors ought to have beenheld liable for losses that resulted from the failure toprevent those violations. The court, in holding thatthe directors were not liable, noted that the claimedbreach relied on "possibly the most difficult theoryin corporation law upon which a plaintiff might hope

to win a judgment." The court found that the direc­tors were simply not liable and had not done any­thing wrong.

Caremark involved the oversight responsibilitiesof directors under Delaware corporate law, and Dela­ware is generally perceived as being the most director­friendly jurisdiction in the nation. For cases in juris­dictions where the law is arguably less hospitable tocorporate fiduciaries, officers' and directors' risks ofbeing held liable may be greater than that suggestedby Caremark. Currently, little case law exists regardingthis issue, at least outside Delaware.

Implications. Brane and Caremark offer guidanceon several important risk management issues, partic­ularly as to derivative-related fiduciary duties. First,prudence is process, not results. The Brane court, forexample, focused less on the content of the derivativeprogram at issue than on the directors' failure toattempt to learn the fundamentals of that program.

Second, before officers and directors (and forthat matter portfolio managers, trustees, and super­visors) decide to authorize the use of derivatives forrisk management purposes, they must possess a suf­ficiently sound understanding of the fundamentalsof the contemplated risk management activity tomake an informed judgment as to its suitabilityunder the circumstances. They do not necessarilyneed to know the details of the mathematics under­lying a derivative program or, for example, how toperform scenario analyses or stress testing, but theymust have a fundamental sense of the economic logicof the contemplated derivative strategy and of thatstrategy's objectives.

Risk Management and Fiduciary Duties

Third, once the directors and trustees decide onthe use of any risk management program, they mustactively supervise and monitor its actual use orimplementation to make sure it complies with theactivities authorized.

Finally, despite what some commentators,including one former chair of the Commodity FuturesTrading Commission, have read into Brane v. Roth,current case law does not suggest that corporatedirectors at times have a fiduciary duty to use deriv­atives to hedge.

ConclusionThe risk of violating fiduciary duties in general, orderivative-related fiduciary duties in particular, neednot be disconcerting. There are compelling reasons toconclude that fiduciary duties apply to derivativeactivities no differently from how they apply to anyother commercially significant economic activity.Most doubts to date have arisen because the two mainbodies of fiduciary law-state corporate law and statelaw of trust investments-offer little specific guid­ance as to how the duties they establish apply toderivatives. Fortunately, the law of trust investmentsthrough the Prudent Investor Rule is undergoing arapid and long overdue modernization that expresslyanticipates the use of derivatives. Under corporatelaw, the shield provided to officers and directors bythe Business Judgment Rule should protect mostderivative-related risk management activities, pro­vided that they are undertaken on an informed basisand subject to appropriate supervision.

29

RiskManagement: Principles and Practices

Question and Answer SessionRobert M. McLaughlin

Question: If a firm has state-of­the-art risk management practices,would that firm be judged by ahigher standard in a court of lawthan a similar firm in similarcircumstances that had not both­ered with risk management?

McLaughlin: I cannot say thatthe first firm would be held to ahigher standard, but it most likelywould be expected to use and takeadvantage of its expertise, espe­cially if the use of that expertisewas broadly advertised or other­wise expressly contemplated byinvestors or entrustors in theiragreements with the firm.

Keep in mind that the firmwithout that expertise would alsobe held to some sort of objectivestandard. For example, supposethe second firm manages invest­ment portfolios and investors spe­cifically complain about the firm'sfailure to use sophisticated riskmanagement techniques. If theinvestors present a compellingcase that the firm ought to be usingthose techniques and that they arereadily available, then there is adanger that the failure to do socould give rise to liability for anysubsequent losses. In any event,whether under trust law or corpo­rate law, the firm would most likelybe held to some sort of standardconcerning the process that itundertakes in evaluating the costsand benefits of its existing riskmanagement systems and the pro­posed new techniques. Prudence isprocess, and a firm that fails toundertake such an evaluationcould easily be seen as failing toexhibit the requisite prudence.

Question: Where are the morefriendly (besides Delaware) andless friendly jurisdictions?

30

McLaughlin: New York, in myview, is a friendly jurisdiction,whether under corporate or trustinvestment law. For example, themost famous derivative case,Procter & Gamble Company v.Bankers Trust Company,1 was anOhio federal court case in whichthe court's decision was based onNew York law. In that case, JudgeFeikens in essence found that P&Ghad no reasonable expectation thatBankers Trust would be acting asits fiduciary; in the terminology ofthe analysis presented earlier, P&Gwas not structurally dependent onBankers Trust for its derivativeexpertise. P&G and Bankers Trustwere parties to a business relation­ship, and Judge Feikens found thatunder New York law, no fiduciaryrelationship can arise betweenparties to a business relationship.?As such, P&G should have expect­ed to be relying on its ownexpertise rather than BankersTrusts', despite Bankers Trusts'"superior knowledge in the swapstransactions." So, this aspect of thedecision was certainly a welcomeone for Bankers Trust and anyother sophisticated derivativemarket participant.

As to trust law, New York hasalso enacted a version of the Pru­dent Investor Rule that, in myview, is highly protective of sophis­ticated trustees. In general, themore hostile environments will bethose states where the new Pru­dent Investor Rule has not beenimplemented.

1925 F.Supp. 1270 (S.D. Ohio, May 9,1996).

2Recently, a New York court asserted that itdisagreed with Judge Feikens' analysis,"inasmuch as a confidential relationshipmay indeed arise between the parties to abusiness relationship." See Societe NationaleD'Exploiiaiion Industrielle DesTabacs EtAllu­mettes v. Salomon Brothers International Lim­ited, QDS: 12101179, New York Law Journal(June 18, 1998):27.

Question: Do stock rights andwarrants require any special docu­mentation?

McLaughlin: They certainly do.Most of the time, stock rights andwarrants are contingent equityclaims that may fall under statesecurities laws, SEC rules, and pos­sibly Commodity Futures TradingCommission (CFTC) regulations.Although no discrete fiduciary lawexists for documenting stock rightsand warrants, standard disclosureand contract rules, SEC adminis­trative rules, and CFTC adminis­trative rules will likely dominateany fiduciary consideration. Andstate anti-fraud law would alsoapply.

Question: Do you see any signsthat the SEC, the CFTC, or the DOLwill be revising its rules to makethem more friendly to modernportfolio theory? Is new legislationby the U.S. Congress likely withrespect to derivative activities?

McLaughlin: The SEC is themost proactive with respect tobringing regulation into line withmodem portfolio theory andinvestment practices. It has pro­posed an entirely new system ofregulating securities activities, anda recent SEC release has attemptedto restructure modern securitieslaw. And although I am not awareof any effort to modify ERISA rulesexpressly to codify the acceptanceof modern portfolio theory, theDOL's benign treatment ofderivatives-recall that in theDOL's view ERISA effectivelytreats a trustee's investment inderivatives in the same way ittreats any other plan invest­ments-may imply the DOL's

general acceptance of modemportfolio theory.

However, the DOL's hands aresomewhat tied by ERISA's statu­tory standard ofcare, which adoptsthe language of the former PrudentMan Rule. That rule is hostile to themodem notion of diversification,the purpose of which is to improvethe efficiency of a portfolio by min­imizing the risk assumed to gener­ate an expected return or bymaximizing expected returns for a

specified level of risk. Unfortu­nately, the applicable ERISA provi­sion, 29 us.c.A. § l104(a)(1)(C),states that the purpose of the diver­sificationrequirement is simply litominimize the risk of large losses";it does not mention improvingportfolio efficiency.

In general, an investment man­ager who is concerned aboutwhether applicable law and regu­lations follow modem portfoliotheory should try to confirm that

Risk Management and Fiduciary Duties

the jurisdiction governing its activ­ities has expressly adopted someform of the Prudent Investor Rule.

Lastly, I do not think Congressis about to pass any new derivativelegislation, at least not in the nearfuture. The CPIC has injected someuncertainty into the area by cham­pioning an effort to reopen much ofthe regulatory debate concerningover-the-counter derivatives, butfew observers think that effort islikely to succeed over the short run.

31

A Behavioral Perspective on RiskManagementAndrew W. LoHarris & Harris Group Professor of FinanceMassachusetts Institute of Technology's Sloan School of Management

Traditional risk management approaches emphasize statistical and economic consider­ations. But comprehensive financial risk management should also incorporate the roleof human preferences in rational decision making under risk.

S ince the market turmoil of August and Septem­ber 1998, skepticism has undoubtedly increased

about the relevance of quantitative techniques for thepractice of risk management. If, as most industryexperts now acknowledge, the general "flight to qual­ity" and subsequent widening of credit spreads wasunprecedented and, therefore, unforecastable, whatgood are Value-at-Risk measures that are based on thestatistics of historical data? These concerns are well­founded but somewhat misplaced in their focus. Thefault lies not in the methods but, rather, in the unre­alistic expectations we have in their application.

In a broader context, rational decision makingunder uncertainty requires a focus on three specificcomponents, which I have previously described asthe"three P's of total risk management": prices, prob­abilities, and preferences.' Although any completerisk management protocol should contain elementsof all three P's, to date most risk management prac­tices have focused primarily on prices and probabil­ities, with almost no attention to preferences. In thisarticle, I will emphasize the role of preferences inrational decision making under risk through threeillustrative examples: the nature of loss aversion, thedifference between risk and uncertainty, and theinterpretation of probabilities.

Before launching into these examples, let meemphasize that despite the term "behavioral" in thetitle of this article, and the increasing popularity of"behavioral finance", the importance of behavior iscertainly not new to modem finance. However, the

1 For a complete discussion of the three P's of risk management,see A. Lo, "The Three P's of Total Risk Management," FinancialAnalysts Journal (JanuaryfFebruary 1999):13-26.

32

enormous progress that psychologists, cognitive sci­entists, and neuroscientists have made in recent yearshas created a renaissance in research on humanbehavior, of which one aspect is economic and finan­cial decision making. This may very well lead to anentirely new field of "financial decision analysis" inwhich the gains from cross-disciplinary research areespecially prominent, and financial risk managementis the obvious starting point.

Loss AversionAn individual's decision making under risk-rationalor otherwise-s-is heavily influenced by the concept ofloss aversion. Suppose you are offered two invest­ment opportunities, A and B:Investment A gives youa sure payoff of $240,000,and investment Bgives youa lottery ticket with a chance of winning $1 millionwith a probability of 25 percent and a chance of win­ning nothing with a probability of 75 percent. If youmust choose between A or B, which one would youprefer? Now investment B has an expected value of$250,00Q-a higher expected value than A's payoff­but this may not be all that important to you becauseyou will receive either $1million or zero. Clearly, thereis no right or wrong choice here; the answer is simplya matter of personal preferences. Faced with thischoice, most people prefer A to B.

Now suppose you are faced with another twochoices, C and 0: Investment C yields a sure loss of$750,000, and investment 0 is a lottery ticket with achance of losing nothing with 25 percent probabilityand a chance of losing $1 million with 75 percentprobability. In this case, C and 0 have exactly thesame expected value: -$750,000. If you must choose

© 1999 Andrew W. La

between these two undesirable choices, which wouldyou prefer (this situation is not as absurd as it mightseem at first glance; one can easily imagine situationsthat require choosing the lesser of two evils)? In thiscase, most people choose D.

These two sets of choices are based on an exper­iment that was conducted by Stanford psychologistsKahneman and Tversky almost 20 years ago.2 WhenKahneman and Tversky performed this experiment,and in many repetitions since then, the results haveshown that an overwhelming proportion of individ­uals preferred A to Band D to C. These choices revealan interesting fact about individual preferences forrisk. For those who choose A and 0, they are selectingthe equivalent of a single lottery ticket that offers thechance of winning $240,000 with 25 percent probabil­ity and losing $760,000with 75 percent probability.fHowever, those who choose Band C (the combina­tion that most individuals shun) have the same prob­abilities of losses and gains-25 and 75 percent,respectively-but when they win, they win $250,000instead of $240,000, and when they lose, they lose$750,000 instead of $760,000. In fact, choice Band Cis equivalent to choice A and 0 plus $10,000free andclear-no risk at all because $10,000 is added to boththe winning and losing alternatives. Faced with thisinformation, would you still pick A and D?

A common reaction to this example is: "It isn'tfair-when you told us about A and B, you did nottell us about C and D." But this example is not nearlyso contrived as it may first appear to be; in a multi­national company, the London office may be facedwith choices A and B and the Tokyo office withchoices C and D. Locally (in London and in Tokyo),there is no right or wrong answer; the choice betweenA and Band the choice between C and D are mattersof personal risk preferences. But the globally consol­idated book for the company will show a very differ­ent story. From the financial perspective, there isindeed a right and wrong answer for the company.The purpose of financial technology is to provide aframework for analyzing problems such as this.Financial technology should prevent people fromengaging in the kind of behavior that gives rise tothese apparent arbitrage opportunities.

20. Kahneman and A. Tversky, "The Psychology of Preference,"Scientific American, vol. 246 (1982):160-173.

3In choosing A, you receive $240,000 for sure. In choosing 0, youlose nothing with 25 percent probability, hence you keep the$240,000, and with 75 percent probability you lose $1 million, inwhich case you are down net $760,000.

A Behavioral Perspective on Risk Management

Risk versus UncertaintyThe distinction between risk and uncertainty is asubtle one but quite important from the perspectiveof the individual investor. The following example,based on the well-known Ellsberg (1961) Paradox.?illustrates that risk management must take intoaccount the uncertainty of risks.

Suppose 100 balls-50 red and 50 black-areplaced into Urn A. You are asked to pick a color, redor black, and write it down on a piece of paperwithout revealing it to anyone. A ball is then drawnrandomly from the urn, and if it is the color youselected, you will receive a $10,000 prize, otherwiseyou will receive nothing. What is the most you wouldbe willing to pay to play this game (this game is to beplayed only once)? Most financial industry profes­sionals name their top price as $5,000, which is notsurprising because this is the expected value of thegame. However, other individuals typically bid con­siderably lower-usually not more than $4,00Q-adiscount from the expected value that indicates riskaversion, a common trait among most of us.

Now consider the same game with the sameterms but with Urn B, which contains 100 red andblack balls of unknown proportion (it might be 100red balls and no black balls, 100 black balls and nored balls, or anything in between). What is the mostyou would be willing to pay to play this game (alsoto be played only once)? The majority of individualsasked say that they would pay much less than theywould to play the first game with Urn A (offers aslow as $100 are not unusual among individuals unfa­miliar with basic probability theory). But this seemsto be wholly inconsistent with the risks of this game,which are mathematically identical to those of thefirst game in which Urn A is used.5

Alternatively, suppose you have already paid$5,000 to play the game but are given the choice ofwhich urn to use, A or B.Which urn would you prefer?Most individuals prefer Urn A, despite the fact that theprobability of drawing a red or black ball is exactly thesame for both urns. This game-a variant of Ellsberg'sParadox-illustrates a deep phenomenon regardingthe typical individual's differing levels of uncertaintyabout his or her risks. How can that be? The words"uncertainty" and "risk" are usually considered syn­onyms, and yet individuals seem to prefer knowingwhat kind of uncertainty they are facing. Somehow,

40. Ellsberg, "Risk, Ambiguity, and the Savage Axioms," QuarterlyJournal of Economics, vol. 75 (1961):643-669.

5For Urn B, you do not know what the proportion is of red/blackballs-you literally have no information. Presumably, what thismeans is that it is 50/50 (this represents the "maximum degree ofignorance").

33

RiskManagement: Principles and Practices

not knowing about that uncertainty is worse thanknowing about the uncertainty. This brings up theobvious question: "Do people care about the uncer­tainty of the uncertainty of the risk?" Unfortunately,we do not yet have a satisfactory answer to this ques­tion, and only recently have researchers begun tostudy this question in the context of financial riskmanagement.

This example is particularly compelling becauseit illustrates all of the elements-the three P's again­that a complete risk management protocol ought toinclude. First, the game requires an understanding ofthe statistics of the phenomenon-that is, the proba­bilities. For the game with Urn A, it is 50/50. For thegame with Urn B, you do not know the proportion,but it also turns out to be 50/50. The second aspect isan economic aspect, or prices. That is, how much areyou willing to pay? Third, and what I argue is themost important aspect, is the personal aspect,namely, how do you feel about the uncertainty sur­rounding the risks?

Interpreting ProbabiIitiesEven a strict focus on the statistical aspect of riskmanagement, namely probabilities, cannot avoid theissue of preferences; how people interpret probabili­ties often interacts with their preferences in peculiarways. Here I illustrate a curious interaction betweenprobabilities and personal preferences and show thatprobability-based risk management analytics can beimproved in concrete ways by incorporating prefer­ence information.

Probability-Based VAR. Value at Risk (VAR)is based on probabilities. In fact, the RiskMetrics doc­umentation defines VAR in the following way:"Value at Risk is an estimate, with a predefined con­fidence interval, of how much one can lose from hold­ing a position over a set horizon.,,6 VAR attempts toprovide a quantitative answer to the question: "Whatis the probability of losing $100 million over the nextmonth, given the current portfolio?"

Although the focus-the probability of extremedollar losses-seems to be straightforward, interpret­ing VAR may raise as many questions as it answers.For example, is VAR based on conditional or uncon­ditional probabilities? That is, does VAR indicate theprobability oflosing $100million on any given day, oris VAR talking about the probability of losing $100

6Morgan Guaranty Trust Company, Introduction to RiskMetrics,4th ed. (New York: Morgan Guaranty Trust, 1995).

34

million after a specific event has occurred, such as a 5standard deviation drop in the yen/dollar exchangerate? How does VAR handle consistency across port­folios and across time? Are the probabilities that areeither imposed or extracted from, say, a derivativesportfolio consistent with a foreign currency hedgingstrategy? Does VAR have any mutual checks to makesure that the VAR probabilities are consistent acrosstime? If the probabilities are not consistent, arbitrageopportunities could arise. Does VAR make use ofprior information or preferences? Any sound riskmanagement framework needs to address these kindsof questions.

Conditional Probabilities. The role of prefer­ences in interpreting probabilities becomes clear inthe following serious example taken from the epide­miology literature: AIDS testing.

Suppose a blood test for AIDS is 99 percent accu­rate. By that, I mean the probability of the blood testturning out positive if you have AIDS is 99 percent,and the probability of the test turning out negative ifyou do not have AIDS is also 99 percent. Now, sup­pose you take this blood test, and the test result ispositive. What is your personal assessment of theprobability that you have AIDS? Do not use any otherexternal information to answer this question; onlyconsider the fact that the blood test is positive andthat this test is 99 percent accurate. Many peoplewould say the probability of having AIDS is 100percent, and most everybody would say the proba­bility has to be more than 50 percent.

But the answer is not given by the 99 percentaccuracy of the test, which refers to the probability ofthe test being positive given your condition. The rel­evant probability is the probability of your conditiongiven the outcome of a 99 percent accurate test. Thedistinction between these two probabilities is veryimportant, and Baye's rule links the two formally.

Specifically, according to Baye's rule, the proba­bility of having AIDS, given a positive blood test, isequivalent to the probability of a positive blood testgiven that you have AIDS, multiplied by the uncon­ditional probability of having AIDS divided by theprobability that the blood test is positive:

Prob(AIDS)Prob(AIDS 1+) =Prob(+IAIDS) x Prob(+) .

To assess your probability of having AIDS given apositive blood test, you need two other pieces of datain addition to the fact that the blood test is 99 percentaccurate: the unconditional probability of AIDS,Prob(AIDS), and the unconditional probability of a

positive blood test, Prob (+), which are approximately0.1 percent and 1.098 percent, respectively? There­fore, the probability that you have AIDS given apositive blood test is:

0.1%Prob(AIDS/+) == 99% x-- '" 9.02%.

1.098%

The relevant probability-the conditional probabilityof AIDS given a positive blood test-is not 100 percentor even 50percent, but 9 percent! This is a surprisinglysmall number given the accuracy of the blood test, butrecall that before testing positive, the unconditionalprobability of AIDS was only 0.1 percent. Testingpositive does yield a great deal of information­indeed, the probability of AIDS increases almost ahundredfold-but it is by no means a certainty thatyou have AIDS.

When we make use of probabilities, we must keepin mind that we need to focus on the right probabili­ties. Moreover, researchers and practitioners need tothink about how simple probabilities interact withother factors, such as conditioning on prior informa­tion (the AIDS example illustrates the importance ofconditioning information). Experience, judgment,and intuition are also critical in assessing prior infor­mation, as are preferences and human biology.

Interpreting Zero-Probability Events. In theAIDS example, if you guessed, as many people do,that the probability of your having AIDS given apositive blood test was 100 percent, you concludedthat the probability that you did not have AIDS waszero, a very strong conclusion. Zero-probabilityevents create interesting conundrums for modernfinance. Suppose an event E has never occurred in thepast. Because of the nature of human cognition, mostpeople will act as if the probability of such an eventis zero, despite the fact that they might be able tocontemplate the occurrence of such an event if asked.

But what if another set of individuals thinks thatthe probability of E is not zero? In that case, at leastone group (and possibly both groups) will be con­vinced that an arbitrage opportunity-a "free lunch"transaction-exists. In particular, the group thatbelieves the probability of E is zero should be pleasedto write a low-cost insurance policy that pays $100

7The unconditional probability is the probability of an eventwithout reference to any other event or information. In this case,the unconditional probability of having AIDS is the probabilitythat any randomly selected individual has AIDS, which is roughlyapproximated by the number of individuals known to have AIDSin the United States (about 250,000) divided by the total U.S.population (about 250 million), which yields 0.1 percent. Theunconditional probability of testing positive then follows from:

Prob(+) = Prob(+IAIDS) x Prob(AIDS) + Probr-l No AIDS)

x [I ~ Prob(AIDS)].

A Behavioral Perspective on Risk Management

million if E occurs and nothing if E does not. As longas this group receives a positive premium for writingsuch an insurance contract, it will be happy to do soand will write as many policies as it can, because thegroup believes that it will never need to payout (sinceit believes the probability of E is zero). However, thegroup that believes the probability of E is positiveshould be pleased to purchase such an insurancepolicy at some positive price. Both groups believethey are receiving a bargain, yet this may be a recipefor financial disaster ifE is indeed something that canoccur, even if it occurs infrequently.

This scenario may seem rather simplistic, butconsider the turmoil in the hedge fund industry dur­ing the summer of 1998. Some of the hedge fundmanagers involved have argued that the events ofAugust and September 1998were unprecedented andvirtually impossible to anticipate. All the relevantmodels and risk analytics indicated that the possibil­ity of such a massive global flight to quality and suchhuge increases in credit spreads was an extraordinar­ily unlikely event (a 27 standard deviation event, bysome accounts). In other words, what actually hap­pened was, ex ante,a zero-probability event!

Such zero-probability events can create somevery serious gaps in risk management systems. Thesegaps are related to the distinction between objectiveand subjective probabilities. That is, if you and I havedifferent probability assessments, then as a practicalmatter, an objective probability may not be relevant.Rather, multiple subjective probabilities exist, andsubjective probabilities are influenced by none otherthan human preferences.

Summary and ConclusionExisting risk management practices focus on the sta­tistical and economic aspects of risk management, anendeavor that should be called "statistical risk man­agement". They do not focus on the personal aspectsof risk management, which is where much morethought and research should be devoted. This sug­gests the possibility of a new approach to risk man­agement-called financial risk management-inwhich the importance of preferences is explicitly ac­knowledged and a serious attempt is made to mea­sure preferences and consider their interaction withprices and probabilities to arrive at optimal financialdecisions. While financial risk management is morechallenging than statistical risk management-itdoes requires additional structure, more sophisti­cated estimation and inference, and more carefulinterpretation-the payoff is a genuine capability ofmanaging, rather than just measuring, financial risks.

35

RiskManagement: Principles andPractices

Question and Answer SessionAndrew W. La

Question: If some guarantor oflast resort will bail people outwhen they have huge losses,should risk management systemsbe adjusted accordingly?

Lo: Not only should people beadjusting their risk managementpractices for the likelihood of abailout, but in practice, people doadjust for it. That is, they take intoaccount the implicit insurance thatthey have at their disposal, whichis a very serious problem thatunderlies not only hedge funds butalso mutual funds and individualsinvesting in Individual RetirementAccounts and 401(k) plans.

This insurance phenomenoneven influences compensation con­tracts for typical managers. Theinteraction between individualpreferences and compensationcontracts is very complex. Forexample, the typical hedge fundmanager has a compensation con­tract that is convex. The managergets a management fee and anincentive fee. The incentive fee cre­ates a bias toward taking on morerisk, and the manager has his or herown preferences that have to belayered on top of the compensationcontract. The problem is determin­ing the overall risk profile whenyou put all those pieces together.

Another way of thinking ofthis problem is to fix the compen­sation contract and the desired riskprofile of the manager. Then, underthese constraints, how many man­agers do you have to interviewbefore you find the one that has theright personal risk preferencessuch that when the individual'spreferences interact with the com­pensation contract, you arrive atthe proper risk behavior? Workingthrough the problem this waymeans that you will have to spend

36

a lot of time thinking about how tomeasure risk preferences, which isone of the projects that I am work­ing on now with psychologists andneuroscientists.

Question: How do you actuallyincorporate a zero-probabilityevent into your models?

Lo: One of the unique abilities ofhuman cognition is being able tocreate a mental model of eventsthat do not exist. Humans have theunique ability to dream up all sortsof bizarre scenarios and ideas andplans and expectations, to plan forcontingencies that have neverexisted. This ability is what allowsus to dominate the environmentthe way we do.

The problem from a risk man­agement standpoint is how manydifferent events do you think thereare that have never occurred butthat might be relevant for the nextfive years? There are many suchevents. What we need to do is touse our creativity, our judgment,our heuristics, in fact, all of ourexperiences to try to come up withevents for which, although theyhave a very low probability ofoccurring, the probability is notzero. For other events, we simplyhave to assign zero probabilities,because we cannot possibly ana­lyze all of these events.

The events of August and Sep­tember 1998 are important notbecause we learned so much aboutspecific details of statistical analy­sis or risk management systemsbut because we learned that some­thing that we thought was not pos­sible was possible. We havebroadened our mindset in terms ofzero-probability events. We needto do a lot more of that mind broad­ening, but in the end, we are never

going to foresee all possible disas­ters that can occur.

Question: In your AIDS exam­ple, what happens if the accuracyof the blood test is 100 percent?

Lo: If the test accuracy goes from99 percent to 100 percent, a lotchanges. If you are saying that thetest perfectly predicts whethersomebody has AIDS, then if thattest is positive, the person definite­ly has AIDS. So, to that person, thedifference between 99 percent and100 percent accuracy is all thedifference in the world!

What is remarkable is that peo­ple simply do not make such finedistinctions. Wedo not distinguishbetween 99 percent events and 100percent events, because we are notstructured to do so. Think abouthuman evolution and how wecame to be able to process the kindof information that we do. We arethe product of hundreds of mil­lions of years of environmentalforces that impinged on our prob­ability of survival. So, do you thinkthat being able to distinguishbetween a 99 percent event and a100 percent event would lead to ahigher probability of survivalwhen you are being chased by asaber-toothed tiger? I doubt it.

What is intriguing, and what Ithink has implications for evolu­tionary biology, is that the probabil­ity of survival in the nextmillennium may well be linked tobeing able to discern between 99percent probability and 100percentprobability. The rise of financialmarkets, financial interactions,financial engineering, and moneyas a medium of exchange and ameasure of "fitness" may influencethe nature of human evolution. Wein finance will have a lot to say to

A Behavioral Perspective on Risk Management

the evolutionary biologists aboutwhat they ought to start learning­the Black-Scholes model and thecapital asset pricing model, forexample--during the next 20 years!

Question: What are the implica­tions of behavioral finance for theinvestment management world?

Lo: One general implication isthe impact of behavioral biases oninvestment decision making. Forexample, there is a differencebetween active management fromthe point of view of pursuing aparticular long-run financial goaland active management that is anoutcome of trading decisions thatare influenced by behavioral bias­es. Humans are extraordinarilyrisk averse when it comes to gains.That is, we believe that a bird in thehand is worth two in the bush. Ifwe are ahead, we want to lock inthose gains. But, when it comes tolosses, we are much more riskseeking. That is, if we are threat­ened with a loss, we would ratherdouble up than take a sure loss.

This behavior is perfectly rea­sonable from an evolutionary per­spective. If your very existence isthreatened, the last thing you willdo is try to calculate probabilitiesand take a loss that would makeyou even less likely to exist. Youwill gamble to try to get out of thatdanger. In investment situations,we are not talking about losing ourlives, but the fact is that our brainsare wired to respond to risk in thatparticular way. One of the experi­ments that I hope to conduct is totake a look at how traders' brainactivities shift as they are facedwith losses versus gains. I want totry to isolate exactly what part ofthe cognitive process is associatedwith these kinds of biases.

In terms of the practical impli­cations of behavioral finance, oneimplication is to focus on risk man­agement with the knowledge thatthese biases exist. Another, which iseven more important, is to educateclients (e.g.,pension plan sponsors)and, ultimately, individual inves­tors about how to think about riskin a more systematic fashion (whichdoes not necessarily mean "in amore rational fashion"). There is

nothing irrational about thesebiases. After all, they are whathelped us survive the past 100 mil­lion years. They are inappropriate,however, in a financial context.Being able to understand whenthese biases are appropriate andinappropriate is critical for dealingwith investment problems. Finally,managers should be thinking aboutthe entire risk management processfrom beginning to end. They shouldthink about risk as a multidimen­sional, multiattribute phenomenonthat needs to be dealt with in amuch more sophisticated manner.In active management, it is not justthe beta or the sigma or the trackingerror that is relevant. What are alsoimportant are draw-downs, thedynamics of the risk and how theyshift through time and acrossregimes, and how correlationsamong various securities change inresponse to institutional and politi­cal changes. This is a very compli­cated task that cannot be completedovernight, but I think that currentresearch will enable us to providesome tools to allow individuals tomanage those risks better.

37

The Plan Sponsor's Perspective on RiskManagement ProgramsDesmond Mac IntyreVice President, Financial PlanningGeneral Motors Investment Management Corporation

A sound risk management program must be grounded in the organization's philosophy,objectives, and mission. General Motors Investment Management Corporation hasintegrated a variety of key criteria-from audit/review to output-into comprehensivebuilding blocks for a total risk management system.

L OOking back and trying to pick the point atwhich an organization first began its risk man­

agement activities is difficult, especially when peoplebelieve strongly that risk management alwaysexisted. In fact, much of the early work that an orga­nization does in developing a risk management pro­gram simply centers on documenting what hasactually happened to that point. Eventually, mostorganizations move to a more structured environ­ment in which explicit objectives are set and practicesare continually documented-in other words, to aformalized point at which it is no longer sufficient tosay that the organization has always operated in aparticular way and everyone knows what that way is.

This presentation discusses the experience ofGeneral Motors Investment Management Corpora­tion (GMIMCo) in building a broadly constructedrisk management program to cover the more than$110billion under its management; included are pro­gram objectives and scope, critical building blocks,key criteria, and potential benefits.

BackgroundThe first step toward setting up a formal risk man­agement structure was taken in 1995, with the forma­tion of an internal risk management task force. Thattask force had a mandate to figure out how GMIMCoshould take a formal approach to risk management;in so doing, the task force members had to confrontseveral issues. For instance, they had to consider theimplications of the dynamics between group respon­sibility and individual accountability, and they hadto consider the cultural aspects of dealing with

38

extremely defined rules on the one hand and anenvironment of trust with minimal definition on theother hand. People were understandably concernedthat a formal program would stifle imagination andcreativity and limit the opportunity sets GMIMComight consider. The task force members also had toconsider the possibility that they would create anapproach and standards that could not be adhered to,thus causing more harm than good.

Two other factors had to be taken into account.First, any risk program or standards must be relevantto both the staff and the investment process and thusget collective "buy-in" across the organization.Although the risk management role must be indepen­dent and protected from interference, involving andeducating everyone with respect to risk issues is abso­lutely critical. Second, any risk management programmust be forward looking. A retrospective viewpointis usually dangerous, inevitably degenerating into a"blame game" and being perceived as a "witch hunt."

After balancing all these concerns, the task forcerecommended the establishment of a risk manage­ment function and the appointment of a director ofrisk management, reporting directly to the presidentand CEO of GMIMCo. With the risk managementfunction in place, then began a process of reviewingindustry best standards and practices, the mostrelevant of which turned out to be the RiskStandards Working Group, with its strong focus onthe end user and institutional investors. Their 20standards helped add momentum to GMIMCo'sinternal efforts and undoubtedly those of manyother organizations as well.

©Association for Investment Management and Research

The PlanSponsor's Perspective on Risk Management Programs

Following this broad sweep of standards andpractices, GMIMCo began to create its philosophy, aset of objectives, and a mission with respect to formalrisk management.

Philosophy, Objectives, and MissionGMIMCo's philosophy and objectives culminated ina mission statement that encompasses the formal riskmanagement approach.

Philosophy. GMIMCo's philosophy begins withthe notion that risk, in and of itself, is not negative.What does have a potentially negative impact on Gen­eral Motors and GMIMCo is the undertaking of riskthat is not properly priced, not managed effectively,and/or misunderstood or simply not known. Second,risk management is a holistic endeavor and must bevery broad based, transcending quantitative andqualitative measures.

Third, all risks must be managed, not just thosethat receive the attention of the press, although it is fairto say that managers who repeat the very visible mis­takes of others probably get what they deserve.Fourth, risk management should be proactive, notreactive. Finally, managing risk is the responsibility ofeveryone in the organization, and one of the dangersin moving to a formal approach is that risk manage­ment will come to be perceived as being the provinceof one or a few"experts."

Objectives. GMIMCo's objectives are threefold:to implement a depersonalized (objective) approachfor evaluating and monitoring current risks within thecontext of an overall program; to sensitize employeesand management to investment and operational risk;and to satisfy General Motors and GMIMCo seniormanagement that risks are known, controlled, andacceptable worldwide.

Mission. From the philosophy and objectiveshas come a mission statement that addresses severalkey elements of the risk management process. First,risk needs to be measured, monitored, and managedwithin a consistent framework under the active over­sight of senior management. In that regard, GMIMCohas set up a risk management committee, which isdiscussed later. The purpose of active oversightshould be to continually determine whether the riskmanagement program is practical, is relevant to ouractivities at GMIMCo, and is not strangling ouropportunities. Second, we need to ensure that we areadequately rewarded for the risks we take. Third, thedirector of risk management should widen the recog­nition of existing and potential risks, should identifythe critical elements of both absolute and relative risk,and should seek and develop appropriate measuresfor both absolute and relative risk.

©Association for Investment Management and Research

Risk Management ApproachGMIMCo's approach to implementing its risk man­agement philosophy, objectives, and mission is afairly standard one. First, the risk director, with broadinput from the rest of the organization, identified andselected suitable benchmarks as a starting point andconducted a firmwide risk audit against those bench­marks. In that regard, we believe that accountabilityis the biggest form of risk control, so we worked toensure accountability for our own standards as theyevolved. The entire framework was clarified; the res­olution of action items necessitated by the risk auditwas benchmarked; reporting lines were clarified;findings, procedures, and policies were well docu­mented; and clear timelines were established, withstated consequences of failing to take necessary riskmanagement actions. One of the comments of the RiskStandards Working Group members was that manyrisk standards are not actually adhered to, so we madeour standards a guidance document of best practiceto steer our future direction and activities.

Circle of Risks. As an organization, GMIMCodeveloped a common framework for viewing thescope of risks, what we call the "circle of concern,"that we face every day. GMIMCo identified 10 keyrisks, as follows.

II Compliance risk. The possibility that existingprocedures do not adequately ensure that GMIMCoand its clients are in compliance with the rules andregulations of governmental and regulatory bodiesand industry standards of practice. Compliance riskalso includes the possibility that the record keepingneeded to document compliance is not sufficient toshow that GMIMCo and its clients are, or have been,in compliance.

III Corporate or financial risk. The potential thatevents and/or decisions at GMIMCo will have anadverse impact on the financial position of GMIMCoitself or its parent, General Motors.

ill Credit/counterparty risk. This risk has twoaspects: (1) the risk of a counterparty's credit deteri­orating, thus substantially affecting the price of thesecurity, and (2) the potential that the issuer of asecurity may default or fail to honor its financialobligations to GMIMCo or its clients.

III Fiduciary risk. The potential exposure of thefiduciaries for each client to legal and regulatoryactions precipitated by a breakdown in controls orfailure to execute due diligence on behalf of the plan.

II Liquidity risk. The potential failure to main­tain sufficient funds, primarily cash and marketablesecurities, to meet short-term obligations. Also, mar­ket liquidity risk is the inability to dose out or liqui­date market positions at fair market value within areasonable time frame.

39

RiskManagement: Principles and Practices

II Monitoring risk. The potential for lossesbecause of unintended bets or a breakdown in duediligence with respect to manager relations, or thepotential for unintended consequences from theresults of investment initiatives that were not fullyunderstood at the outset.

III Operational risk. The potential for discontinu­ity because of the possibility of a breakdown in oper­ational procedures, particularly as they relate to aprocess breakdown; this risk is distinct from thedesign, implementation, and maintenance of com­puterized information systems.

II Market risk. The possibility of loss resultingfrom movements in market prices (e.g., from changesin interest rates, foreign exchange rates, volatility,correlations between markets, or capital flows).

l1li Modeling risk. The potential for loss becauseof actions taken or of policies implemented based onviews of the world, in general, and the investmentcommunity, in particular, that are derived fromimproper models. These views are derived from rep­resentations of reality that do not capture all signifi­cantly relevant information or are inappropriatelyapplied throughout the investment program.

II Systems risk. The potential that current sys­tem designs or implementations are inappropriate orineffective to the extent that information obtainedfrom or disseminated through the system environ­ment is incorrect or incorrectly perceived and there­fore, the potential that the decisions made based onthat information are suboptimal. In addition, this riskincludes the security of information in response tounauthorized access and the continuity of opera­tional and information system capability in the eventof a disaster.

Circle of Influence, Once we identified thescope of risks facing GMIMCo, the task team thenlooked at the extent to which GMIMCo could influ­ence and/or control for these risks, which we call our"circle of influence." For each risk, we tried to definethe best industry standards for that particular risk,and we defined a road map to translate those stan­dards into best practice. Recognizing that not all risk­influencing goals were obtainable short term, weprioritized action items. We tried to relate best prac­tices to the different needs of each product and eachbusiness unit and to fit those practices into the orga­nizational culture.

For example, to try to influence or control moni­toring risk, we focused on the portfolio impact ofmanagers' violating investment guidelines or engag­ing in unauthorized transactions, excessive concentra­tions, or outright fraud. Under the standards of bestpractice for monitoring risk, we addressed risk­adjusted performance, risk limits, stress testing, return

40

attribution, investment profiling, due diligence, opti­mal structures, target tracking errors, informationratios and alphas, benchmarks, and new productreview groups-e-essentially putting together an entirestructure from which to monitor and review our ongo­ing investment program for internal and externalmanagers.

Training, To translate these standards to ourorganizational culture, we held workshops in eachbusiness unit. Although GMIMCo has six businessunits, divided along asset class groupings, many ofthe risks are common to all groups. After meetingwith one or two groups, we came up with about 80percent of the risks we believe we face as an organi­zation. We categorized our risk exposures as eitherhorizontal or vertical. Horizontal risks are qualitativein nature: the operational risks involved in financialaccounting and controls, legal, personnel, research,and systems. Vertical risks (corporate, modeling,market/credit, and liquidity risk) are quantifiableand specific to a particular asset class, thus differingfrom business unit to business unit. By looking at therisks as horizontal and vertical, we were able to deter­mine our organizational exposures quite quickly, totranslate standards and practices consistently acrossthe organization, and to get collective "buy-in" as weimplemented our program.

BUilding Blocks of RiskManagementGMIMCo's formal approach to risk management canbe viewed as consisting of systematic building blocksarranged on five rows, as shown in Exhibit 1.

The first row of building blocks begins with areview of objectives and resources, with respect to riskmanagement. Small firms might be faced with nothaving enough resources, but external resources canbe leveraged, via consultants, risk bureaus, and thelike. We then proceed (horizontally in the first row) toan understanding of best practice and how relevantthat practice is to our organization's unique opera­tions. Having established best practice (and receiving"buy-in" from management, which is important), thenext step is to review, audit, and document existingoperations versus best practice. The final step of thefirst row is to prioritize, based on the audit results, theareas where actions are needed. The emphasis shouldbe on what is feasible and achievable and on guardingagainst unrealistic expectations.

The second row of building blocks in Exhibit 1focuses on management considerations. First is cor­porate governance-the process and structure bywhich client and corporate objectives are met.GMIMCo is currently in the midst of an exercise inwhich we have identified every major decision in our

©Association for Investment Management and Research

ThePlan Sponsor's Perspective on Risk Management Programs

Exhibit 1. Building Blocks of Risk Management

Review: Objectives/Row 1 Resources Best Practice Review / Audit/

DocumentPrioritize

Action

Row 2

Row 3

CorporateGovernance

Asset-LiabilityReviews

InvestmentPrinciples/Objectives

Risk LevelsAlpha Targets

ManagementStructure/

Accountability

InvestmentControl

Framework

BusinessContinuity

Selection Criteria:New Products/

Managers

Row 4Data: Performance Monitoring/

Source/Validation/ Measurement/ ExceptionValuation Attribution Reporting

EscalationProcedures

RowS Benchmarking Education IndependentReview

Review: Objectives/Resources

organization, the key information points required tomake that decision, and the people responsible forimplementation and oversight. For an investmentorganization, a key building block obviously must becontinual consideration of investment principles,objectives, and philosophy. Management structureand accountability is particularly important to ensureconsistency in approach and process across assetclasses. Business continuity touches on severalissues, from disaster recovery planning (who is deal­ing with year 2000 issues?) to succession planning(who is going to replace the head of a business unit?).

The third row of building blocks focuses oninvestment-specific issues and revolves around howto translate corporate and fiduciary objectives into anasset mix. Asset-liability reviews are critical;GMIMCo conducts asset-liability reviews every threeyears for General Motors' U'S. pension plans, in addi­tion to an annual validation of the investment policyguidelines stemming from the review and the capitalmarket inputs used. For each asset class, and obvi­ously in the context of the asset-liability process, wehave identified certain return targets and trackinglimits versus those targets. In tum, we have relatedour incentive compensation structure to those alphatargets. We have also established a consistent invest­ment control framework covering investment philos­ophy, fund construction, and analysis. Finally, at thislevel, we have increasingly formalized the new prod­uct development criteria and the selection criteria weuse to hire new managers. This step has become evenmore important recently with the evolution of exoticinstruments.

The fourth row of building blocks in Exhibit 1deals with performance measurement for risk man-

©Association for Investment Management and Research

agement purposes. Obviously, a key element of anymeasurement system is the data being used andreported; trust in the source and validation of thedata quality are absolute necessities. GMIMCo hadseveral custodians in place for all of our assets untilrecently, which made gathering all those data a hugeexercise. We have recently consolidated to two cus­todians and implemented a master record-keepingstructure so that, in essence, we are building a datareservoir from which to work. If the data are notcleaned up and validated, the exercise of modelingdata at the aggregate level is time consuming at bestand certainly of questionable value at worst.

We have a similar stance with respect to perfor­mance measurement and attribution. We are activelylooking for standardization in performance attribu­tion across all of our asset classes, and we are stan­dardizing to the extent possible all performancemeasurement analytics across all of our asset classes.We have recently commingled our defined-benefitand defined-contribution assets, and 50 percent ofour assets are now valued in the daily net asset value(NAV) environment. Although this change to a NAVenvironment brings with it a whole new set of risks,increased transparency and daily performance mea­surement are important advances for us.

Once a program is in place, monitoring that pro­gram and reporting exceptions in some formal waybecomes a necessity. Many organizations have auto­mated exception reporting systems. GMIMCo has anentire set of procedures and standards for reviewingmanagers on a semiannual basis, with set agendas forthose manager reviews. We have also engaged in theexercise of involving people from different asset

41

Risk Management: Principles and Practices

classes to review certain managers. The simple, basic,and direct questions from someone who is not famil­iar with a certain asset class can often be the mosttelling. In all cases, the focus is on documenting andrecording all of this information and holding our­selves accountable. If the monitoring process revealsa breach, whether internal or external, escalation pro­cedures, such as error and omission policies, thencome into play. A key reason why the risk programhas to be independent is that it has to report to topmanagement to avoid potential interference in theseescalation procedures.

The fifth and final row of building blocksattempts to ensure that the entire risk managementsystem "completes the loop" with respect to contin­uous feedback and review. Benchmarking progressshould be done against peers, against stated objec­tives, and against the best standards that have beenadopted. Risk management education should be con­tinuous. Our legal staff and our investment staff holdinternal workshops in which we work through ideasand annual workshops in each business unit in whichwe go over the relevance of our risk managementsystem. Independent reviews need to be integratedinto the system. A formal annual audit process is agood first step in this regard, whether internal orexternal. Finally, the right-most building block in thefifth row actually ends the process where it began­review of objectives and resources-although in thiscase, the review is conducted in light of changingmarket conditions, the changing use of products, andchanging risk appetites and objectives.

Key CriteriaAny organization embarking on a formal risk man­agement program should recognize the key successcriteria, which can be organized into four categories:audit/review, dependencies, required managementresponse, and output.

Audit/Review. This category includes identify­ing and internalizing best practice, engaging in aninteractive risk review, prioritizing action items,tasking individuals and making them accountable,and benchmarking the resolution of items. It is espe­cially important in the review process to engageeveryone in the organization, questioning each per­son about every aspect of his or her business as itrelates to risk exposure and risk control.

Dependencies. The dependencies criteria referto the necessary resource and system requirements.Centralized and aggregated information systems arecritical, especially to those organizations whose oper­ations are global. Knowledge and continuous educa­tion are key, as are clear communication, marshalling

42

of necessary resources, total group involvement, andardent and visible management support.

Required Management Response. Not only ismanagement support critical, but certain manage­ment responses are also required periodically. Clearlystated risk management objectives and a well-definedand up-to-date plan, a solid organizational structure,a meaningful reporting format that cannot be"gamed," clear accountability, periodic assessment(i.e., review, benchmarking, and recalibration), andclear linkage of risk performance to compensation­all of these must be seen by management as requiredcomponents of an effective risk management system.

Output. A risk management system's perfor­mance can be judged by its output, by the tangibleevidence of its existence. Such evidence may includemore-defined and better-documented control pro­cesses and overall control environment, writtenacknowledgment of responsibilities, documented riskand return limits and objectives, risk templates forvarious investment programs, established reportingand escalation procedures, and a centralized risk man­agement platform from which to run a continuous riskmanagement cycle. GMIMCo's experience providesnumerous examples in two key areas-structure andreporting--of this risk management system output.

II Structureexamples. With respect to structure,an internal valuation committee was established sothat we would have hierarchical price structures andrules for every single asset class. The previouslynoted risk management committee-a broadly basedgroup consisting of people from investments, seniormanagement, controls, legal, and other areas-meetsquarterly with a set agenda to consider. This commit­tee has well-defined reports to analyze, which givessome degree of independence and protection to therisk manager, and it reports on an annual basis to ajoint committee of GM Corporation and GMIMCo. Aformal risk management team is now in place and hasrecently been expanded in size, and all risk manage­ment objectives are linked into the investment man­agement process.

We have developed educational programs andworkshops and hold annual group risk workshops,in which we review what has been achieved in thepast year and give people the opportunity to voicetheir concerns-in the spirit of asking them to expresstheir concerns going forward, not dwelling on mis­takes made in the past. We have formalized escala­tion procedures and developed errors and omissionpolicies and funding arrangements for such policies.We have consolidated our custodial structure andnow basically operate off the platform of a masterrecord keeper, and each of our fund managers hasaccess to all of the daily data.

©Association for Investment Management and Research

The Plan Sponsor's Perspective on Risk Management Programs

III Reporting examples. With respect to reporting,GMIMCo has adopted a value at risk (VAR)approach that is supplemented appreciably withscenario analysis-regarding our derivative andforeign exchange activities-for liquidity manage­ment and assessing counterparty risk. We havestandardized review formats for all of our externaland internal managers. We have also set up ad hocreviews for external managers, in which we get amixture of investment, control, and risk managementstaff to visit the external manager and assess theentire organization-from the research departmentto the trading process to the formalization andconstruction of portfolios.

We have documented and standardized ourinvestment philosophy, processes, and proceduresorganizationwide. We have also reviewed our invest­ment guidelines. In one asset class, for instance, wehad 350 investment rules, of which probably 20 wereappropriate. The review caused us to focus anew onwhat is important to the client and what is critical to

©Association for Investment Management and Research

our business, rather than on setting up multiple rulesjust to be seen as"in control." We have also developeda process for reporting and resolving exceptions.Finally, we have set up quarterly benchmarkingagainst our objectives and developed consolidated,independent risk management reporting.

ConclusionRisk management is not about generating a risk num­ber. It is about setting up a quality control environmentin which everyone is encouraged to ask questions andgenerate solutions and in which everyone is a riskmanager. Developing and formalizing a risk manage­ment program provides clear business benefits. Sucha program strengthens and supports the decision­making process, increases senior management's com­fort level and awareness, helps identify risk exposuresand especially opportunities, strengthens compliancewith regulatory requirements, and in general, pro­motes a stronger, more effective control environment.

43

Risk Management: Principles and Practices

Question and Answer SessionDesmond Mac Intyre

Question: What have been thebiggest surprises from establishingthis risk management program?

Mac Intyre: I am somewhat sur­prised by the unintended benefitsand by the willingness of everyoneto get involved. Better communica­tion is probably one of the mostvaluable results of setting up aprogram such as this. You have toget together all the various strandsand different viewpoints in yourorganization, and what becomesvery clear are the different mind­sets, different philosophies, andindeed different appetites for risk.

The formalization and stan­dardization of the process has alsobeen a valuable benefit. In all hon­esty, having risk standards in aninformal capacity as part of yourinvestment process is dangerousand actually makes investmentmanagers' jobs more difficult, notless. If you can formalize the areasin which they are asked to act, thatsituation is better and cleaner forinvestment managers; we havefound their reactions and involve­ment to be Widespread and posi­tive. Far from being resistant, theinvestment personnel are theactual designers of our risk man­agement program.

Question: In what ways doesthis program affect your externalmanagers?

Mac Intyre: First, we do notabdicate the responsibility foranalysis ourselves. We have estab­lished rigorous reporting require-

ments for our external managers,but we want reporting to beindependent and internalized. Weare, however, ultimately responsi­ble for that analysis ourselves. Infact, one of the main reasons thatwe developed our internal man­agement activity was so that thosepeoplecould better understand themanagers they were managing; forexample, we have a Europeanportfolio manager who is responsi­ble for European managers.

Second, we have standardizedthe review format. All of our exter­nal managers are subject to semian­nual review, and all of our internalmanagers are subject to quarterlyreview. In those reviews, we have afixed agenda that we ask all of ourinvestment personnel to workthrough every meeting. Also, inmoving a large portionof our assetsto a daily NAV environment, wehave (1)set in place more-rigorousstandards in terms of reconcilia­tion, (2) set pricing hierarchies forvarious asset class and securities,and (3)established a three-way pro­cess that involves GMIMCo, itsexternal managers, and custodians.

Third, the risk managementteam gets involved in the selectionof external managers, not to serveas a roadblock but to become famil­iar with the risk exposures and riskrequirements that might be uniqueto that relationship. Finally, com­munication is key. Whether indeveloping guidelines or under­standing objectives, our relation­ships with external managers haveto be a two-way process, and oftena simple conversation will clear up

a miscommunication or a lack ofunderstanding.

Question: Other than VAR,what measures do you use toreview market risk?

Mac Intyre: To a degree, weencourage everyone to look at abroad set of risk measures. At theportfolio level, we have alphatargets, and we look at multiplerisk measures, such as trackingerror and semi-variance data.Although we often hear that thebest set of risk measures is one thatcould be standardized, there is stillsome value in profiling managersfrom different perspectives andusing different shortfall measures.It is also important that any riskmeasure, and any risk measure­ment product, have total buy-in atthe portfoliomanagerlevel. We areworking with several vendors toestablish an aggregate platformfrom which to view portfolio risk,asset class risk, and total plan risk

Question: How have you incor­porated risk into the compensationscheme for internal and externalmanagers?

Mac Intyre: Everyone's com­pensation and/or bonus is in partqualitative and in part quantita­tive. To a degree, the risk elementis contained in the qualitativemeasure, which reflects the factthat we started off with a moreholistic rather than quantitativeview of risk management.

44 ©Association for Investment Management and Research

Managing Risk in the Industrial CompanyCharles W. SmithsonManaging DirectorGIBe World Markets

Industrial companies are important users, albeit with a different perspective frominvestment firms, of risk management products. Using such products, especially forcompanies with certain characteristics, should and apparently does reduce risk andincrease company value.

I nterest in the uses and applications of risk manage­ment products (especially those involving deriva­

tives) has been sharpened by derivative-relatedheadlines, mostly negative, during the past severalyears. Exhibit 1 shows the losses associated withderivatives by type of company in each year from 1994through 1998. At different times, nonfinancial users,institutional investors, and dealers have all felt thesting of huge derivative losses. In that context, whatU.S. industrial corporations do to control risks hasapplications for what pension funds and money man­agement firms should be doing to hedge their risks.CIBC World Markets has been carrying out researchfor a long time on the risk management practices ofnonfinancial companies because we sell risk manage­ment products (i.e.,derivative products) to these com­panies (see Bodnar, Marston, and Hayt 1998).1

This presentation discusses the use of risk man­agement products by industrial corporations, exploresthe theoretical arguments for why risk managementproducts should add value, and examines the avail­able empirical evidence on whether risk management"works"-that is, if a company uses such products, doits risks diminish and!or value increase?

Use of Risk Management ProductsWith the Wharton School, CIBC has carried out threesurveys of industrial companies' use of derivativessince 1994.Of the full sample of surveyed companies,35 percent reported that they used derivatives in1994,41 percent in 1995,and 50 percent in 1998.Theseraw numbers imply that use is increasing, but if only

IComplete information on CIBC's surveys and research is avail­able on the School of Financial Products' World Wide Web site:www.schoolfp.cibc.com.

© 1999 Charles W. Smithson

the companies that responded to at least two of thethree surveys are examined, the level is flat-at about41 percent for respondents to three surveys and 44percent for respondents to two surveys. Althoughuse of derivatives by industrial companies has notincreased, neither has it decreased in the wake of thehorror stories in the WallStreetJournal and elsewhere.

Moreover, for those companies that do use deriv­atives, the level of usage is up. When asked in the1998 survey about the intensity of their use of deriv­ative products, 42 percent of respondents reportedthat use had increased over the previous year, 46percent reported use had remained constant, andonly 13 percent reported use had decreased.

Users and Uses of Derivatives. The surveyresults indicate that large companies are by far thebiggest users of derivatives. In the 1998 survey byBodnar et al., 83percent of the large companies (thosewith fiscal year 1996 total sales greater than $1.2billion), 45 percent of the medium-sized companies(sales between $150 million and $1.2 billion), and 12percent of the small companies (sales less than $150million) that responded use derivatives. That resultis surprising because theory suggests that small com­panies would benefit more from these products thanlarge companies. The reason, however, could be thatmanagers of the small companies are not as familiar,and thus not as comfortable, with derivative prod­ucts as their larger company counterparts. As busi­ness schools increasingly make derivatives a part oftheir regular curricula and companies, regardless ofsize, move up the learning curve, the numbers for useby small companies should grow.

As for the businesses of the companies usingderivatives, the 1998survey indicates the greatest use

45

Risk Management: Principles and Practices

Exhibit 1. Losses Associated with Derivative Products, 1994-98

Nonfinancial Users

1994Coldeco ($207million)

Gibson Greetings ($20 million)

Procter & Gamble Company($157 million)

Mead ($7 million)

Air Products and Chemicals, Inc.($70million)

Federal Paper ($19million)

Caterpillar ($13million)

1995

1996

1997

1998

Institutional Investors

Askin Capital Management

Arco ($22 million)

Investors Life Insurance Company($90 million)

Piper Jaffray

Odessa College ($11 million)

Orange County, CA ($1.5 billion)

Wisconsin Investment Board ($95 million)

Escambia County, FL ($19 million)

Common Fund ($138 million)

Dealers

Barings Securities ($1 billion)

Sumitomo Corporation ($2.6billion)

NatWest Markets ($127 million)

Bank of Tokyo-Mitsubishi ($53 million)

VBS ($431 million)

J.P. Morgan & CO.

IBJ($120 million)

Salomon Brothers ($100 million)

Peregrine Holdings Limited

Salomon Smith Barney ($700+ million)

Bankers Trust Company ($488 million)

Nomura Securities International ($1.16billion)

Goldman, Sachs & Company

VBS ($600 million)

Westdeutsche Genossenschafts-Zentralbank($230 million)

by primary product companies, which include agri­culture, mining, energy, and utilities (at 68 percent),followed by manufacturing companies (at 48 per­cent), and service companies (at 42 percent).

Industrial companies use derivatives to reduce avariety of exposures, but the most frequent use is forreducing foreign exchange risk. The 1998survey indi­cates that 81 percent use derivatives to manage for­eign exchange exposure, 67 percent to reduce interestrate risk, and 42 percent to manage exposure to com­modity prices. So, the kind of nonfinancial companymost likely to be using derivatives is one that isinvolved in foreign exchange transactions.

Instruments. Nonfinancial companies use vary­ing combinations of options, forwards, futures, andswaps-both exchange traded and O'TCc-dependingon the exposure being managed. The 1997 CIBC/University of Waterloo survey of Canadian industrial

46

companies-the sister survey to the Wharton surveydiscussed by Fortin (1998)-indicates that forwardsare the favorite product of industrial companies formanaging foreign exchange risk. The likely explana­tion is that those companies are using aTC forwards tohedge transaction exposures (i.e., to lock in the valueof receivables or payables). Forward contracts, by theway, are also the tool most widely used by institu­tional investors for managing foreign exchange risk.

For managing interest rate risk, industrial compa­nies tend to favor interest rate swaps, an aTC product.In contrast, institutional investors favor exchange­traded futures contracts. This difference arises fromthe basic nature of the business that each type of firmconducts and the investment horizon each faces.Investment firms are in the business of securities andderivative trading, and their investment horizon isrelatively short. Institutional investors, therefore, liketo use exchange-traded instruments in case they need

to get out of a position quickly because they know theyare likely to find the liquidity they need on theexchanges. Industrial companies only use derivativesto facilitate their real business, and their horizons canbe quite long. So, even though few dealers offer thecustomized OTC products and such positions are, asa result, harder to unwind than futures, the interestrate swap market is so large that a major and relativelylong-lasting market disruption is the only potentialproblem for those industrial companies that tap thatmarket.

For managing commodity exposure, industrialcompanies prefer forwards and, to a lesser extent,options.

Reasons for Use. The 1997CIBC/University ofWaterloo survey asked industrial companies aboutthe objectives of their derivative use. The respondingcompanies indicated that their"most important objec­tive" was managing cash flows (nearly 40 percent ofthe respondents), followed by managing earnings (25percent) and minimizing financial distress (almost 15percent). The respondents indicated that their "sec­ond most important objective" was managing cashflows (about 25 percent), followed by minimizingfinancial distress (more than 20 percent) and manag­ing earnings (more than 15percent). Companies iden­tified their "third most important objective" to bereducing market risk (about 25 percent), followed bymanaging cash flows, minimizing financial distress,and maintaining a competitive position (all about 15percent each).

The point is that these companies tend to bemanaging some kind of flow measure rather than astock measure. Value at risk (VAR), by contrast, is astock measure that was developed inside banks as away of communicating between the trading desksand senior managers. VAR is valuable for OTC deriv­ative dealers and managers because they are inter­ested in value changes, whether an absolute changeor a rate of change. VAR is much less useful for mostindustrial corporations because they do not managetheir companies in terms of present value; they man­age in terms of having sufficient cash flows this quar­ter to meet an investment budget or to pay a dividend,for instance.

How Can Risk ManagementIncrease Firm Value?Should the shareholders of industrial companieswant the companies to practice risk management?The answer is simple: They should only if risk man­agement can increase the value of the company.

One reason risk management might increase thevalue of the company is through reducing the risk to

ManagingRisk in the Industrial Company

shareholders. Risk management products change thevariance of returns; the expected net present value ofa swap or an option or any other financial product atorigination (leaving out the bid-offer spread) is zero.Derivatives reduce volatility, but portfolio theorymakes clear that they are useful only to the extent thatinvestors cannot diversify their risks in other ways.If risks were completely diversifiable, nobody wouldneed or want these products.

The true value of risk management products tothe shareholders of widely held firms is found in thework of Merton Miller and Franco Modigliani. Theso-called M&M Proposition 1 is as follows: In a worldof no taxes, no transaction costs, and a given, speci­fied investment decision, the debt-equity structure ofa corporation does not matter. The proposition isactually even broader. In such a world, no financialpolicy-to issue common or preferred stock, to man­age risk or not-matters. But in fact, financial policydecisions do matter in the real corporate worldbecause such decisions have an impact on (1) thetaxes the company pays, (2) the transaction costs, and(3) the investment decision.

So, a shareholder has a stake in whether the firmhedges or not. If the firm can hedge in such a way asto reduce its tax liability or reduce its cost of financialdistress, the shareholder should be pleased becausethe shareholder cannot achieve those effects as anindividual investor. Those effects can only beachieved at the firm level. The most important reason,however, for the shareholder to care about a firm'sfinancial policies is that investment decisions are notfixed; the firm may be able to improve its investmentdecisions. At the simplest level, the shareholderwould like the firm to make the following investmentdecisions: Accept all projects with positive netpresent values, and reject all projects with negativenet present values. In short, if risk management canmove the firm toward those decisions, shareholderswant the firm to practice risk management.

Suppose a hypothetical U.S. company, AcmePharmaceuticals, is exposed to foreign exchange raterisk, interest rate risk, and commodity price risk. Thecompany's biggest exposure is foreign exchange riskbecause it is a U'S. dollar-based firm that sells drugsin all of the countries of the world and has royaltiescoming in from all over the world. All those foreigncurrencies are eventually converted into Ll.S, dollars,so when the dollar is strong, Acme's pretax cash flowswill be low. When the dollar is weak, Acme's pretaxcash flows will be high. Its cash flows are definitelyvolatile. On average over time, if Acme does nothingabout the volatility, its cash flows will be at the mean.Why would Acme go to a derivative dealer that willcharge it half the bid-offer spread to move the cashflows toward the mean sooner than if the company

47

Risk Management: Principles and Practices

simply waited for the flows to settle on the mean?Acme cares about this volatility because if it doesnothing about it, the volatility can change the econom­ics of this company. The issue Acme is worried aboutis that if the dollar is strong enough, its cash flows willbe low, and if the cash flows drop low enough, thatdrop will trigger a cutback in R&D spending. A phar­maceutical company does not want to cut R&D, thelifeblood of its revenue and income stream.

To generalize, risk management could increasethe value of a company by reducing its taxes if thecompany has more tax loss carryforwards, more taxcredits, and!or more income in the progressive(higher marginal rate) region of the tax schedule.Similarly, risk management could increase the valueof a firm by reducing the costs associated with finan­cial distress (a specific transaction cost) if the firm hasless interest coverage, more financial price risk, moreleverage, and!or lower credit ratings. Finally, riskmanagement could increase the value of a firm byfacilitating its optimal investment decisions if thefirm has more R&D expenditures and!or a highermarket-to-book ratio.

Academic research has generated both theoreticalpredictions and empirical evidence with respect to thesigns of these determinants of risk management use.The consensus predictions from 3 theoretical papersand the consensus evidence from 15 empirical studiesare shown in Exhibit 2. Note that the empirical evi­dence supports the theoretical predictions.

Based on this empirical evidence, what kind ofcompanies would be more likely to use derivativeinstruments? The answer is companies with more taxloss carryforwards, more tax credits, less interestexpense coverage, more leverage, and higher R&Dbudgets.

Researchers have also examined agency relation­ships in companies that use derivatives. A companythat wants its managers to work hard is likely tomotivate them with the reward of either shares oroptions on shares. All other things being equal, whois more likely to manage risk-the option receiver orthe share receiver? Put another way, which of the twolikes volatility? The option holder likes volatilitybecause it increases the value of that option position.Theoretically, if managers are compensated withoptions, one would expect them to do less hedgingthan managers who are compensated with actualequity. Consistent with theory, Tufano (1996) andother researchers (Ceczy, Minton, and Schrand 1997;Wysocki 1996; and Berkman and Bradbury 1996)found a positive relationship between equity com­pensation and level of hedging. Tufano also found anegative relationship between option compensationand level of hedging. Gay and Nam (1998) found theopposite relations, and Ceczy et al. also found a pos­itive relationship between option compensation andhedging activity, so the empirical evidence is mixed.

Does Risk Management Work?Although theory predicts that risk managementshould work, the real question is whether risk man­agement does work. That is, do risk managementproducts contribute to lower risk, higher share price,and!or improved investment decisions?

Risk. In a study of whether companies that userisk management products actually reduce their risk,Guay (1999) examined changes in company risk fornew users of derivatives according to three measuresof risk-total risk, interest rate risk, and foreignexchange rate risk. Table 1 summarizes Guay's

Exhibit 2. Signs of Determinants of Risk Management Activity: ConsensusTheoretical Predictions and Empirical Evidence

Signs

To reduce taxesTax loss carryforwardTax creditsIncome in progressive region of tax schedule

To reduce cost offinancial distressInterest coverageInterest rate or foreign exchange riskLeverageCredit rating

Consensus TheoreticalPrediction

IndeterminateIndeterminateIndeterminate

NegativePositivePositiveNegative

Consensus EmpiricalEvidence

PositivePositive

Indeterminate

NegativePositivePositive

Indeterminate

48

Tofacilitate optimal investmentR&D expenditures PositiveMarket value/book value Positive

Note: For a list of the studies used to compile this exhibit, see Smithson (1998).

PositivePositive

Table 1. Mean Changes in Risk for New Users ofDerivatives (from Year t-1 to Year t)

Type of Risk Mean Change

Total risk -0.56%

Interest rate risk -0.14*Exchange rate exposure -0.25*

"Statistically significant at a 90 percent confidence level.

Source: Guay (1999).

results: All three measures of risk were lower, by atleast 9 basis points (bps) and by as much as 72 bps,after risk management products were used.

Tufano (1998) examined the effect of risk man­agement on gold mining companies. He measuredthe sensitivity of the company's share value to theprice of gold and found that companies that werehedging their gold price risk exhibited less gold pricerisk than companies that did not.

What about Beta? One might question whetherthe preceding results represent diversifiable or nondi­versifiable risk. Interest rate risk, foreign exchangerisk, and commodity price risk are all diversifiablerisks. For example, if investors know a company haspositive interest rate risk, they can diversify theirportfolios by holding the stock of a company that hasnegative interest rate risk. So, what should happen tobeta if the firm uses risk management? Theoretically,nothing should happen to beta, but the empiricalresearch that has looked at beta has found that betabecame smaller. What is causing a change in beta? Theanswer could be that the capital asset pricing modelis wrong and that the market prices risk other thanmarket risk. But the answer could also be that inves­tors are using risk management as a signal of manage­ment quality.

Share Price. Allayannis and Weston (1998)studied the relationship between a company's use offoreign exchange derivatives and the value of thefirm. Their results, as summarized in Table 2,suggestthat the values of those companies that hedge theirforeign exchange risk are higher than those of com­panies that did not use risk management.

In his ongoing research on gold mining firms,Tufano has been examining the effect of risk manage­ment on the stock price performance of gold miningcompanies. He has formed portfolios of gold miningfirms that hedge and portfolios of gold mining firmsthat do not hedge and has tracked the performanceof these portfolios during the 1990s.Not surprisingly,in periods of falling gold prices, the hedged firmsoutperformed the unhedged firms. What is surpris­ing is that in periods of rising gold prices, when theunhedged firms would be expected to outperform

Managing Risk in theIndustrial Company

the hedged firms, the two portfolios exhibited essen­tially the same performance. The reasons are not clearand could be several, but one plausible explanationis that the hedging activity is a signal to investors ofquality of management and of lower overall risk, andinvestors react positively to that signal, even whenmarket price movements are seemingly inopportunefor hedging.

Several years ago, Chris Turner and I were inter­ested in the way that a company's stock price reactswhen the company announces a risk managementinitiative (see Smithson 1998). To examine this ques­tion, we looked at a sample of 158 hybrid debt issues(i.e., debt issues that could be decomposed into astandard debt issue plus an embedded derivative).These hybrids were indexed to interest rates, foreignexchange rates, commodity prices, or other financialindexes. As the preceding evidence indicates, whenthe firm issued the hybrid, the markefs perception ofthe riskiness of the firm changed. We separated oursample into those hybrid debt issues that were likelydone for risk management motives ("risk managers")and those that were not ("others"). We found that thereaction to the hybrid issuance for the risk managerswas positive and marginally significant and that thereaction for the others was negative but statisticallyinsignificant.

Investment Decisions. Minton and Schrand(forthcoming 1999) considered why a shareholderwould want a company to manage risk. For example,why would the shareholders of a pharmaceuticalfirm want the firm to manage its foreign exchangerisk? One possible explanation is that those investorsdo not want the pharmaceutical firm to cut back onR&D.Minton and Schrand examined the relationshipbetween earnings volatility and investment. Theyfound a negative relationship between earnings vol-

Table 2. MeanValueofTobin's Q: Firms That UseForeign Exchange Derivatives versusThose That Do Not, 1990-95

Firms That Use Firms That Do Not UseForeign Exchange Foreign Exchange

Year Derivatives Derivatives Difference

1990 1.53 1.28 0.25a

1991 1.63 1.39 0.24a

1992 1.41 1.21 0.20a

1993 1.42 1.17 0.25a

1994 1.29 1.12 0.17a

1995 1.22 1.13 0.09a

Note: Comparison of median market values.

aRank-sum test indicates P-value less than 0.05.

Source: AIIayannis and Weston (1998).

49

Risk Management: Principles and Practices

atility and investment, implying that if companiescan reduce their cash flow volatility, their capital,R&D, and advertising, then expenditures all increase.

ConclusionA number of theoretical and empirical studies haveprovided insight about the use of risk managementproducts by industrial companies. In the UnitedStates, about half the companies-both large andsmall-are using risk management instruments, pri­marily to manage cash flows and earnings. Lookingat the survey data more closely, one can see that largecompanies are more likely to use risk managementproducts than small companies and primary produc­ers are more likely to use the products than manufac­turing or service firms.

ReferencesAllayannis, George, and James Weston. 1998. "The Use of ForeignCurrency Derivatives and Firm Market Value." Working paper.University of Virginia (lanuary),

Berkman, Henk, and Michael E. Bradbury. 1996. "Empirical Evi­dence on the Corporate Use of Derivatives." Financial Management(Summer):5-13.

Bodnar, Gordon M., Richard C. Marston, and Greg Hayt. 1998."1998 Survey of Financial Risk Management by U.S. Non-FinancialFirms." Wharton School and CIBC World Markets (Iuly).

Fortin, Steve. 1998. "University of Waterloo Second Survey ofCanadian Derivatives Use and Hedging Activities." In ManagingFinancial Risk,Yearbook 1998.Edited by Charles W. Smithson. NewYork: CIBC World Markets.

Gay, Gerald D., and [ouahn Nam. 1998. "The UnderinvestmentProblem and Corporate Derivatives Use." Financial Management(Winter):53-69.

Geczy, Christopher, Bernadette Minton, and Catherine Schrand.1997. "Why Firms Use Currency Derivatives." Journal of Finance(September):1323-54.

50

Theory predicts that risk management couldincrease firm value if it (1) reduces the firm's taxliability, (2) reduces the firm's transaction costs (e.g.,the costs associated with financial distress), and (3)optimizes the firm's investment expenditures.

The available empirical evidence suggests thatrisk management works. Companies that use theseproducts are less risky by several measures of risk andalong multiple risk dimensions-total risk and finan­cial price risk, as well as possibly market (beta) risk.And to the extent that risk management reduces thevolatility of the firm's cash flows or earnings, empir­ical evidence of an association with higher levels ofinternal investment spending has been obtained.Finally, and most importantly, the payoff in shareprice performance to risk management is positive.

Cuay, Wayne. 1999. "The Impact of Derivatives on Firm Risk: AnEmpirical Examination of New Derivative Users." Journal ofAccountingand Economics Uanuary):319-351.

Minton, Bernadette, and Catherine Schrand. Forthcoming 1999."The Impact of Cashflow Volatility on Discretionary Investmentand the Costs of Debt and Equity Financing." Journal of FinancialEconomics.

Smithson,Charles W. 1998."Questions Regarding the Use of Finan­cial Price Risk Management by Industrial Corporations." CIBCSchool of Financial Products Web site (www.schoolfp.cibc.com).

Tufano, Peter. 1996. "Who Manages Risk? An Empirical Examina­tion of Risk Management Practices in the Gold Mining Industry."Journal of Finance (September):1097-1l37.

--.1998. "The Determinants of Stock Price Exposure: Finan­cial Engineering and the Gold Mining Industry." Journal ofFinanceGune):1015-52.

Wysocki, Peter D. 1996. "Managerial Motives and Corporate Useof Derivatives: Some Evidence." Working paper. Simon School ofBusiness, University of Rochester.

Managing Risk in the IndustrialCompany

Question and Answer SessionCharles W. Smithson

Question: Traditional invest­ment management firms, whichrely on index funds and mutualfunds, tend to be publicly owned,whereas hedge funds tend to beprivately owned. Does somethingin the nature of risk managementtools explain this difference incorporate structure?

Smithson: The different corpo­rate structures have evolvedbecause of asymmetrical informa­tion. Ifa firm is following an index,it needs no special information, soit can have a broad, shareholder­managed structure. By contrast, afirm that has valuable informationdoes not want to disclose thatinformation to shareholders, whowant to see it before they buyshares. So, a firm that wants to telloutsiders as little as possible aboutits risks will not go public.

How many financial institu­tions are willing to report theirvalue at risk numbers on theirfinancial statements? The answeris many, and in the next five years,even if the U.S. regulators do notrequire VARreporting, nearly allfinancial institutions will reportVAR numbers in their annualreports. Publicly traded firms can­not afford not to report it. Whenshareholders receive an annualreport that does not contain a VARnumber, they think either the num­ber is so big the firm does not wantto disclose it or the firm does notknow how to calculate VAR. Nei­ther reaction is good for the firm.

Consider what happened withindustrial corporations. The firsttwo companies to report VAR intheir annual reports (which hap­pened in the same year) were Brit­ish Petroleum and Mobil Oil. Why?Because both were known to beactive traders-i-Bl" in the foreignexchange markets and Mobil inhedging interest rate risks. If aninvestor knows that BP is activelytrading foreign exchange, thatinvestor wants to know BP's VARnumber. The same situation affectsinvestment firms. Publicly tradedfinancial institutions that are goingto be active derivative traders willhave to disclose VAR.

Question: Do you think regula­tory pressure and events such asthose that occurred in the creditmarkets during the summer of1998will cause changes in the wayVAR is measured and reported?

Smithson: VAR was originallydesigned to answer the simplequestion of how much risk is in agiven portfolio. It was a shorthandway of conveying whether riskwas a lot or a little. Rather thanbeingconcerned about whether weall had wrong VAR numbers in thesummer of 1998,which by the waywere wrong in the right direction,I am more troubled by VAR beingused in ways that were neverintended and are not appropriate.VAR is primarily a tool forcommunication but is being usedas a tool for control. For instance,using VAR as a stop-loss measureis a problem. When you use VAR

as a stop loss, if you exceed yourVAR today, you are required toliquidate that portfolio startingtomorrow. That liquidation simplyincreases the volatility in themarket even more, which meansthat your VAR will get broachedagain tomorrow, and the negativecycle is now established andintensified, all because you usedVAR inappropriately.

I am also troubled by state­ments in the press such as lithemodels didn't work in the summerof 1998." At CIBC we generated aregular VARnumber, but we alsostress tested our VAR;we looked atother scenarios and knew whatkind of losses we could end up withif those unusual states of the worldcame about. We made a businessdecision that those scenarios werenot going to happen, and we leftinvestment positions alone. Whathappened is that one of those sce­narios we thought would not hap­pen did happen. So, all we could dowas say, "Rats!" We all wish it hadnot happened, but the situation didnot catch us by surprise, and welost what those models said wewere going to lose under those cir­cumstances. The models worked;we simplymadebusinessdecisionsthat did not turn out the way wehoped. The real question for thefinancial institutions that wereusing these models is: If you lostmore than your one-day VARsug­gested you were going to lose, wasyour loss within the bounds of yourstress test? If the answer is yes, thenyour model worked.

51

Practical Issues in Choosing and ApplyingRisk Management ToolsJacques LongerstaeyVice President, Co-Head-Risk Management GroupGoldman Sachs Asset Management

Effective risk management encompasses many concerns and requires a complete pro­gram of organizational capabilities. Defining risk, agreeing on and critiquing measuresof risk, and deciding whether to buy or build a risk management model-all are keysteps in choosing and applying risk management tools.

R isk management systems range from the overlysimple to the numbingly complex. Somewhere

in between is the appropriate approach to riskmanagement for most investment managementorganizations-an approach that addresses key riskexposures with understandable risk measures in auser-friendly risk management model. This presen­tation focuses on some of the practical issuesinvolved with trying to implement a risk manage­ment framework-issues that include defining risk,agreeing on risk measures, recognizing deficienciesin such widely used measures as tracking error, anddeciding whether to buy or build the appropriate riskmeasurement models.

Effective Risk ManagementGerald Corrigan, former president of the New YorkFederal Reserve Bank, described risk management asgetting the right information to the right people at theright time. His description is more telling than itsbrevity might suggest. The "right information" refersto having enough, but not too much, information.Many risk management reporting systems getbogged down in a mass of information, and the dan­ger is that the system will produce data that are notactionable. Portfolio managers and the firm's seniormanagement-the "right people"-need data andinformation that they can act on, which is why andhow the risk measurement group in an organizationcan add value. The "right time" is not always easy toidentify, particularly when someone has to look at thepros and cons of different methodologies and differ­ent systems. The trade-off is frequently between accu­racy and speed. Often, some accuracy must be

52

sacrificed in order for the information to be actionableby management. That trade-off is part of where theart meets the science.

Asset Manager Risks. Many of the risks borneby asset managers are similar to those borne by otherfinancial institutions: performance risk, credit risk,operational risk, the risk of fraud, and business con­centration risk. What differentiates asset manage­ment firms from other financial institutions is thatsome of these risks are shared with clients. In thatcontext, the distinction between the risk that a clientis taking in a portfolio and the risk that the manageris ultimately bearing is inevitably a blurry one, andthe safest posture for the manager may well be to actas if he or she were managing personal funds.

Another way to draw the distinction betweenrisk management for other financial institutions andrisk management for asset management is to contrasttactical and strategic risk management. MichelleMcCarthy focused on the tactical part of risk manage­ment.! The strategic part of risk management, how­ever, asks what performance risk is in a particularportfolio, in a series of portfolios, or in the wholeorganization. The risk management group of an assetmanagement firm also has a responsibility to focuson the business risks that the firm is exposed to. Theultimate business risk is that the firm has so manyportfolio losses that, over time, the firm's client basestarts to diminish.

For example, value at risk (VAR) models areimportant to our broker / dealer business at GoldmanSachs Asset Management (GSAM) for estimating

lSee Ms. McCarthy's presentation in this proceedings.

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Practical Issues in Choosing andApplying Risk Management Tools

how much we can lose in our trading books. Thebiggest potential risk to us as an institution, however,is not the loss incurred by a trading desk. The biggestpotential risk is a sustained bear market that affectsour entire initial public offering business. That risk issubstantially bigger for us, or any other bank on WallStreet, than the trading losses that we incur as a resultof market movements.

Concerns. Risk management encompassesmany concerns, and many systems need to be put inplace to reflect those concerns adequately. Probably ofgreatest importance for a risk management group towork effectively is to make senior management ade­quately aware of the workings of the group. If seniormanagement does not "buy-in" to the process, the riskmanagement group will either have no power or noth­ing to do. Unfortunately, often an "accident" has totake place to ensure management awareness.

If a firm wants to implement a comprehensiverisk management program, it should also• follow "best practices" that already exist in the

industry,• have independent monitoring of positions,• make sure no conflicts of interest exist among the

various people in the investment process,• undertake independent price verification of

inventory and contracts to ensure adequateliquidity,

• establish processes for controlling exposure tooperational, legal compliance, credit, and repu­tational risks (what we call Wall Street Journalrisk), and

• understand the potential market and perfor­mance risks.

Establishing a Program. Four basic ingredi­ents comprise a top-notch risk management group:culture, data, technology, and process.

II Culture. The essence of an appropriate cul­ture is organizational acceptance of risk managementcontrol principles and the development of a "lan­guage" of risk. Still, the risk management culture isvery difficult to define; I often say that it is one ofthose things that I know when I see it. The risk cultureis affected by the "soundness" of the hiring processand the types of risk-reward policies in place. In agood risk management culture, the people through­out the organization are conscious of the risk issuesand the performance risk issues resulting from anyof their decisions. For example, at GSAM, our objec­tive is to produce consistent, stable, replicable returndistributions. Achieving that objective can be hard todo when managers accept absolutely every bench­mark that every consultant can think of, because noone can effectively monitor performance risk versus

©Association for Investment Management and Research

a large number of benchmarks. For funds that have acustomized benchmark, we may not be able to calcu­late the tracking error because we might not knowthe composition of the benchmark. This risk wouldnot be picked up by a VAR model, but it is somethingto be aware of, and we are trying to sensitize every­body in the organization to that problem.

Creating culture is a long process, and it startswhen people are hired, which is particularly difficultin a rapidly growing organization. For example, weoften rotate new analysts through the risk manage­ment group for a period of three months. They areassigned a variety of tasks, and we hope that theyforge links with the risk management group that willlast over time. We organize internal seminars to makepeople aware of certain types of risk exposures thatwe have. We have also created a risk committee thatmeets every two weeks in which the business headsof all of the areas meet, review performance, discusssubjects related to risk management in general, andmake presentations to the risk committee on theirown specific activities. The goal is to try to create aculture in which the portfolio manager is the personresponsible and the risk group serves as the safety net.

II Data. Position data, market data, factor data,historical return data-a risk management grouprequires a variety of data in seemingly huge quanti­ties. The more data we get, the happier we are becausethen we can design anything we feel comfortablewith. But those data need to have high integrity andmust be integrated with respect to historical returns,current positions, and the analytics being under­taken. Thus, a risk management group is a significanttechnological investment, and fortunately, the assetmanagement world is slowly overcoming its histori­cal reluctance to spend money on risk management.

II Technology. A risk management group needsa system that captures, analyzes, and distributes riskinformation. Although a lot of systems do a good jobcapturing and analyzing risk, very few systems do agood job distributing that information and format­ting it for people who actually need to manage risk.One often gets the impression that the people whodesigned the reports have never managed a portfolio.At GSAM, we spent a reasonable amount of timeredesigning reports to identify what is really goingto hit us in our risk systems, what Bob Litterman callsthe "hot spots" in a portfolio.f

II Process. The final ingredient for establishingeffective risk management is designing a process toput in place appropriate responsibilities, limits, pol­icies, and procedures. Much of this work is common­sense, but the details can be overwhelming.

2Robert Litterman, "Hot Spots" and Hedges," Journal of PortfolioManagement (December 1996):52-75.

53

RiskManagement: Principles and Practices

Defining RiskAt GSAM, the first step in managing risk is to definewhat performance risk means for a particular client.For example, should the focus be on absolute VARorrelative VAR (i.e., tracking error)?3 Although thosetwo concepts are so similar that they are often diffi­cult to distinguish, they do differ in terms of thehorizon and level of confidence used. Typically, theclient defines the exact risk measure, but even whenthe client defines the risk measure, does the clientabsolutely, always want to use that risk measure? Ifclients say that they are measuring performance rel­ative to a particular benchmark, will it always betrue? Certainly, many portfolio managers argue thatmeasuring performance relative to a benchmark isvalid on the upside but often not on the downside.On the downside, clients basically look at perfor­mance versus cash. So, measuring against a bench­mark will not work in all cases. In some cases,implementing an absolute risk measure, as well as arelative measure, is a good idea.

In addition to risk defined against a benchmark,certain clients stipulate that managers have to beat thecompetition. From a risk management perspective,beating the competition is difficult, because knowingexactly what the competition is doing, or even in somecases who they are, is difficult. Trying to beat thecompetition is like trying to manage against a bench­mark without knowing its composition. Therefore,the relative risk is an unknown, and one cannot adda lot of value to an unknown.

For a particular fund, we must also determine ifrisk is symmetrical. Distributions might be skewedbecause the fund has derivative positions, and evenabsent derivative exposure, certain markets, such asemerging markets, can create fat-tail distributions.Looking at just one number is not enough; the wholedistribution of returns has to be examined.

Clients must thoroughly understand what therisk measure means, no matter whether we or theclient selected that measure. Even if we are not usingtracking error and are using something that is scaledto the 99th percentile, does the client understand thata 1 percent chance of loss is not the same as never,especially given that the 1 percent chance alwaysseems to happen in the first quarter that the moneyis under management?

Thus, the educational process that we gothrough with clients and others within the organiza­tion is quite important. Our risk management groupworks with the marketing group and clients to makesure we are all speaking the same risk language. Most

3Formore information, see the Goldman Sachs Asset Managementreport "Tracking Error: VARby Any Other Name."

54

of us in the risk management group at GSAM camefrom the banking or brokerI dealer risk managementside, so we had to learn and adapt to the terminologyused in investment management. One of the firstthings we did was establish a glossary, and in doingthat, we discovered that many people were using thesame term to mean different things, which is itselfanother source of risk for an organization. For exam­ple, variance to me is a statistical term; it does notmean the difference in performance between a port­folio and its benchmark.

Finally, clients and managers must be clear as towhether performance matters more than consistency.That question is a philosophical one. Although I donot have the definitive answer, I lean toward consis­tency; some people favor performance. Performanceand consistency are basically two different productofferings. Therefore, the risk management frame­works that an organization puts in place for both ofthose things may differ.

Risk MeasuresAfter defining the performance risk issues, the nextstep is to make sure that everyone agrees on the riskmeasure used. Agreement, however, is an all­encompassing term, and an in-depth look at track­ing error serves to illustrate the difficulties inherentin settling on a certain risk measure and the impor­tance of being able to objectively critique any spe­cific measure.

Tracking Error. Tracking error is probably themost commonly used measure of performance risk,but does everyone agree what tracking error actuallyis or how it is calculated? Tracking error can becalculated in different ways; are we going to look athistorical tracking error or forecast tracking error,and what type of model is going to be used? Supposea client gives us tracking-error guidelines. If the clientasks us to measure compliance risk, we would needto go back to the client and ask what he or she means.In this context, what does having 500 basis points(bps) of projected tracking error mean? Dependingon which VAR system we run the portfolio through,we can get hugely different results. Thus, we can bein compliance with one system and not in compliancewith another, so what does compliance risk mean tothis particular client?

Tracking error also does not provide insightsinto "one-sixth events"-those events that are in thelower left-hand tail of a portfolio distribution andthat are going to affect the value of the portfolio aboutone-sixth of the time. So, the risk management groupmight need to put other indicators in place, in addi­tion to tracking error, to monitor risk. For example,

©Association for Investment Management and Research

Practical Issues in Choosing andApplying RiskManagement Tools

the group might want to look at style drift to makesure that managers are in line with their mandates orwith their typical strategies. The group may alsowant to look at consistency of performance acrossaccounts, which is more of a strategic risk manage­ment consideration, particularly for those concernedwith the replicability and scalability of their business.Finally, the risk management group might want tolook at short-term changes in correlations versus thebenchmark to see whether certain portfolio managersare starting to drift away from their mandates and/or their benchmarks. Another way to look at thisproblem is style analysis.

Deficiencies in Methodology. Although manypeople are quick to cite the failures and shortcomingsof VAR, tracking error actually suffers from most ofthe same shortcomings, because it is partially thesame methodology. The evaluation horizon for assetmanagers is typically longer than that for traders, butit is shorter than the investment horizon. Thus, dis­tinguishing between an investment horizon and anevaluation horizon is important. A manager mighthave a 5- or Ifl-year investment horizon, but peopleare going to look at the manager's performance everythree months or even more frequently. I have heardof managers getting calls from clients on the 20th ofthe month asking why the portfolio has underper­formed 200 bps since the beginning of the month.Unfortunately, even if managers have a long invest­ment horizon, they must look at risk measures thatare consistent with their somewhat shorter evalua­tion horizons.

The 1 standard deviation measure that is typi­cally used does not intuitively provide managerswith the probability or size of underperformance inthe case of event risk. Even ifa manager does not haveoptions or complex derivatives to manage, some dis­tributions may not scale normally from the 1, 2, or 3standard deviation level. This phenomenon is partic­ularly true for emerging market portfolios, whichtend to have fat-tailed return distributions.

Any tracking error represented by one numberdoes not give managers a good idea of what a client'sutility function is. Utility function is one of thoseconcepts in economics that has always been intu­itively understandable but very hard to measure. Amanager can phrase questions in certain ways todetermine how clients feel about this particular thingor how they feel about that particular thing. In thisway, the manager can come to a closer understandingabout the outcomes that would make the client panicversus the outcomes that, if they happen, would beacceptable.

©Association for Investment Management and Research

Another problem with using tracking error isthat clients typically have asymmetrical responses toperformance in rising and declining markets. Thatasymmetry has a significant bearing on how a man­ager might structure a client's portfolio. If a clientdoes not reward a manager as much for outperfor­mance compared with how much the client penalizesthe manager for underperformance, the managermight use a strategy that caps the upside and protectsthe downside. The problem is that a dichotomy oftenarises between a client's utility function and theinvestment guidelines. Ifa client has strong risk aver­sion on the downside, that aversion argues for usingderivatives to protect the downside, but often, a cli­ent's guidelines indicate that options cannot be used.The potential conflict is quite clear.

Tracking error, by definition, reflects relativereturns, which are questionable if, as is usually thecase, the benchmarks do not represent the client'sliabilities. We assume that whatever benchmark weare given to manage against is the appropriate repre­sentation of the client's liabilities, but that assumptionis often not true. Although our role is not to second­guess our clients, we still try to model those liabilitiesand make sure that whatever investment performancewe are asked to generate is consistent with those lia­bilities and with the benchmarks. Even so, tracking­error forecasts are often a function of the benchmark.A manager can calculate tracking error versus anybenchmark, but if the client's portfolio is composed ofdifferent securities from those in the benchmark, thetracking-error number can be meaningless.

The resulting tracking-error number is exposedto substantially more model risk than the number thatthe manager would get from assuming that the bench­mark looks very much like the portfolio. For example,suppose you are managing a fund versus the S&P500Index and you have only S&P 500equities in the fund.A reasonable assumption for this fund is that thecorrelations have less risk of breaking down (remem­ber that the equities are all part of the same universe)than if you were managing a small-capitalizationfundagainst a large-cap index. When a small-cap fund ismeasured against a large-cap index, at times thosesecurities will be correlated and the tracking error willbe low, but when a significant event occurs, thosecorrelations will break down and the tracking errorwill rise significantly. Therefore, the appropriatenessof benchmarks becomes a key issue in assessingwhether the tracking-error measure is meaningful.

Deficiencies in Models. Another problem withtracking error is that many of the estimates generatedby the models vary significantly depending on theparticular model used. For example, using daily

55

Risk Management: Principles and Practices

returns for a U.s. growth and income equity fund forthe period January 1997 to January 1999, the annual­ized historical tracking error is 796 bps. Figure 1shows that the tracking error for rolling 20-day peri­ods is between 5 percent and 10 percent on average,although it did exceed 15 percent in January 1999.With monthly data, the tracking-error estimate isabout 530 bps, but that number is probably affectedby the sample size, which is only 24 observations fora two-year sample period. Monthly data for a longerhistorical period show that the tracking error movesback to about 775 bps. The question then becomeswhich tracking-error number is correct, and theanswer becomes a judgment call depending on whatthe risk manager thinks the fund is currently doing.For example, I have a tendency to focus on short-termmovements. Therefore, I am biased toward looking atthe higher numbers, particularly because the 20-dayrolling tracking-error number has drifted up in thelatter part of the sample period. But the tracking-errornumbers are ambiguous and raise as many questionsas they answer.

Figure 1. Rolling 20-Day Historical TrackingErrorof a U.S.Growth and Income Fundversus the S&P 500 Total Return Index,1997-99

25r------------------,

20

c.... 150........~

IJO.s 10..>:uttl

~

5

O'----'----'----'-_-'-_---'-_---'__.L..-_..J..J

1/97 4/97 7/97 10/97 1/98 4/98 7/98 10/98 1/99

One question we might ask, for instance, iswhether style drift explains why the tracking errorwent up at the end of the sample period or whethersome more-fundamental change was at work. Figure2 shows the 20-day rolling return correlation for thesame growth and income fund against the S&P 500and the 20-day rolling correlation between the S&P500 and theS&P 500 Value Index. up until November1998, the two lines followed each other closely.Because the correlation between the S&P 500 and theS&P 500 Value Index did not suffer the same dissoci-

56

Figure 2. Rolling 20-Day Return Correlations,1997-99

0.9

0.8to:0

0.7..0..$~.... 0.60

U0.5

0.4

0.3 '--_-'--_--'-_---'-_--'-_---'__.L..-_-'--_--'-'

1/97 4/97 7/97 10/97 1/98 4/98 7/98 10/98 1/99

- us. Growth and Income Fund versus S&P 500

.... S&P 500 versus S&P 500 Value

ation evidenced in Figure 1, the idea of the trackingerror going up because of style drift is probably notappropriate. If I were monitoring the risk of this fund,these data would be a signal to talk to the portfoliomanager and determine the causes of the spike intracking error.

Tracking error, either historical or prospective,will not identify issues, such as extreme events, thatinvolve the whole distribution of returns, which iswhere simulations can contribute information. Fig­ure 3 shows the distributions of monthly variancesfor historical returns and the current positions basedon Monte Carlo simulations We included a series offunds across different asset classes, some of whichactually used derivatives, to make sure the distribu­tion would not be totally symmetrical. We first sim­ulated the historical distribution of the aggregate ofthe funds' returns, shown by the solid line. Then, wereran the simulation, shown by the dotted line, usinghistorical data on the instruments in the funds butusing the funds' current positions. The dotted lineshows that the risk has been significantly reduced:The distribution is narrower, and although it still hasa kink on the left-hand side, the distribution does nothave the fat tail that the solid line has. Thus, thecurrent fund positions are less risky than the histori­cal fund positions. This view of the total risk of theportfolio could not be achieved by looking at trackingerror alone.

Risk managers must make their clients aware thateven if a fund has a constant tracking error over theyear, during the year, the fund might spend some timeoutside that return distribution. Figure 4 shows thetracking-error levels for a fund that seeks to outper­form the benchmark by 3 percent annually with a

©Association for Investment Management and Research

Practical Issues in Choosing and Applying Risk Management Tools

Figure 3. Distributions of Monthly Variances Using Monte Carlo Simulations

...

Current Positions

Historical Returns

-2.0 -1.6 -1.2 -0.8 -D.4 o 0.4 0.8 1.2 1.6 2.0

Return (%)

Figure 4. Vear-to-Date Cumulative Returns for U.S. Equity Growth andIncome Fund versus S&P 500 by Target Tracking-Error Levels, 1998

Expected Return-----~-----------~---

+1 Tracking ~~~~r .......................

............... :':1' T;~~ki~g E~roi B'.·

........

Equity Fundversus S&P 500

A

-3 Tracking Error ----I."T,::~~-----------

30

20

10

~e...- .....a 0.8'"~

-10

-20

-30Time

tracking error of 6 percent. At the end of the year, thefund's return will hopefully lie at Point B, which iswithin the predetermined tracking-error level. Withinthat year, however, the fund spends some time out­side that distribution, in area A.

The fund shown in Figure 4 (the heavy solid line)was managed versus an established benchmark. Overthe course of 1998, the fund's performance, as mea­sured by tracking error, degraded substantially. Butthe benchmark was inappropriate, and therefore, the

©Association for Investment Management and Research 57

RiskManagement: Principles and Practices

tracking-error estimate was probably not a good indi­cation of the overall risk.

Backtesting. Backtesting is one way to assessthe accuracy of tracking-error forecasts. To createFigure 5, we ran a U'S. growth and income fundthrough a tracking-error model developed by a soft­ware vendor and then back tested the model's results.We found that the model performs relatively poorly;13 percent of the observations are outside the 2.33tracking-error band.

In the banking sector, backtesting is taken veryseriously, and models typically are not released untilthey are adequately back tested. This backtesting hasnot been the case in the investment managementindustry, but backtesting will simply have to becomea more important aspect of model design and devel­opment. In the meantime, portfolio managers oftenintuitively or subjectively, on the basis of their ownexperiences, adjust model risk estimates.

Strategic Perspective. To achieve consistencyof performance, which is important at the strategicmanagement level, the investment firm might wantto measure factors that are totally unrelated to track­ing error. Figure 6 shows the distributions of monthlyrelative returns for two account categories. We took

two series of client accounts that are managed thesame way and created histograms of their distribu­tions. Panel A shows a distribution of returns that isvery tight around its mean. These accounts are for themost part being managed consistently. The distribu­tion in Panel B is scattered, even though the accountsshould be managed in a consistent fashion, andrequires further investigation. Although there couldbe some good reasons (client guidelines, restrictedstocks) why the distribution is scattered in Panel B,there could also be some reasons that are not as defen­sible and that would require a change in process. Afirm that has made a strategic decision to strive forconsistency of performance wants to have distribu­tions similar to those in Panel A, not Panel B.

Strategic Risk Management Measures. Firmsalso want to make sure that their fund performanceis not affected by credit concentrations or by a firm­wide style bias. Credit concentrations may not beimportant on a portfolio-by-portfolio basis but mayhave substantial liquidity implications in the aggre­gate. Also, firms do not want to be betting their busi­ness on what investment asset class is, or will be, instyle in any particular year. Firms do not want to bettheir franchise, and their ability to attract or retainassets, on things that they cannot control.

Figure 5. Weekly Returns for a U.S. Growth and Income Equity Fund versusS&P 500 Returns, November 14,1997, to November 20,1998

•

•

•

.......

•

-

.Ii!' .

•

• ••

....... ..•.......... "

-1 Tracking Error

-2.33 Tracking Error

•+2.33 Tracking Error

•

.... . ........

• • •• • +1 Tracking • ••..... Error •.................... .

.............•o -~if' .~~ .•.h..I!!..~.;.,.h.. ..,.._., ..IL IL.

• •...............~0.5

-1.0

2.0

1.5

1.0

'E0.5

OJ~OJ

0...

•10/16/988/21/986/26/985/1/983/6/981/9/98

-1.5 '-------'---------'-----'-------'-----------'-------'---'-------'11/14/97

• Weekly Returns

58 ©Association for Investment Management and Research

Practical Issues in Choosing and Applying Risk Management Tools

Retum(%)

Retum(%)

rest. The primary disadvantage of building a systemis the large investment in cost and time; the primaryadvantages are flexibility, hopefully increased accu­racy and precision, and competitive differentiation.Manager A cannot tell a client that he or she managesrisk better than Manager B if they are both using thesame vendor-generated analytics. This competitivedifferentiation will help to separate the top assetmanagement firms from those in the second tier.

The advantages of buying a system are relativelylow cost and support from the provider, but atGSAM, we find that the market is not very large ordiverse for providers of performance risk analyticsand reporting systems to the investment manage­ment industry. As a result, this scarcity of providershas affected the quality not only of the analytics butalso of the reporting software. A number of the sys­tems have decent analytics, but they do not necessar­ily work all the time, and the system architectures areusually difficult to adapt. So, at GSAM, we built ourrisk management system, which uses different com­ponents from different vendors and some internallydeveloped applications, basically combining riskmodels from third parties and what we use internallyon the broker/ dealer side. So, we have the GSAM risksystem as the framework and the delivery system,but any portfolio can be run through a variety ofexternal or internal risk models.

ConclusionA practical approach to risk management recognizesthe investment risks that need to be measured, theorganizational concerns that need to be addressed,and the elements of a meaningful program-eulture,data, technology, and process. Those organizationsthat are able to define their relevant performancerisks, agree on measures of risk that avoid some of theserious deficiencies of widely used measures, andassess the trade-offs involved in buying versus build­ing risk measurement models are most likely to imple­ment a truly useful risk management system.

/

A. Account Category 1

B. Account Category 2

I

Figure 6. Distributions of Monthly RelativeReturns for Two Account Categories

Buy or Build?My personal recommendation for creating a riskmanagement system is to buy the best and build the

©Association for Investment Managementand Research 59

Risk Management: Principles and Practices

Question and Answer SessionJacques Longerstaey

Question: Do you change yourmethod of risk management de­pending on the fund you arelooking at?

Longerstaey: I believe in stick­ing with one overall approach torisk management, although the ap­proach might be modified for eachtype of product and perhaps fordifferent clients. Over time, how­ever, you want to ensure stability.By using one approach, you knowits shortcomings, and even if theabsolute number has some faults,as the number evolves over time, itwill become ever more meaningfulbecause you can make consistentcomparisons and judgments.

Because different variations ofan approach may be used for dif­ferent asset classes, the aggrega­tion is particularly important andcomplex. You might, for instance,use one type of factor model forlooking at equities and a totally dif­ferent factor model for looking atfixed income. Thus, aggregatingthe data is typically a problem. For­tunately, at the aggregated level,people are less concerned with theabsolute pinpoint accuracy of thatrisk measure and more concernedwith the big picture.

Question: Do you use a stan­dard tracking-error number?

Longerstaey: We have spent areasonable amount of time withour portfolio managers and ourmarketing people to position ourproducts so that we have adiversified product offering. Adiversified product offering meansdifferent levels of trackingerror fordifferent products for differentclients. For example, the trackingerror for a Japanese equity fundvaries substantially depending on

where it is distributed. The track­ing error might be lower if thatfund is distributed as a componentof an international equity fundthan if the same fund is distributedlocally in Japan. Internationalinvestors would be looking forgeneric exposure to the Japanesemarket, but domestic Japaneseinvestors would be looking formore-aggressive risk taking. Thetrackingerror depends onhow youposition your fund and whichclient you are dealing with.

Question: Do you use risk­return ratios in your analysis?

Longerstaey: The risk manage­ment group works with manage­ment to develop performancemeasures, such as risk-returnratios or information ratios, forportfolio managers and to ensurethat everybody feels comfortablewith those measures. The numberthat everybody thinks they canachieve for long-only portfolios is0.5. That is, for a 3 percent returnover the benchmark, 6 percent riskis a good guideline.

One of the first things we didwas to look at whether that ratio ismeaningful and which part of thepercentile distribution the ratio liesin. On the active equity side, a man­ager with a 0.5 information ratio isa star-in the top percentile of thedistribution. But also keep in mindthat there is likely to be a relation­ship between how many managersare pursuing a certain strategy orsector or style and the ability toachieve a 0.5 ratio. Other managertypes would have substantiallydifferent ratios; a hedge fund man­ager, for instance, might be able toachieve information ratiosbetween 1.2 and 3.

Question: How do you view thecomparative advantages of a his­torically based VAR perspective, aMonte Carlo simulation, or anoth­er kind of parametric method?

Longerstaey: We all use his­tory. The one big advantage thatthe different versions of paramet­ric and Monte Carlo methods haveover pure historical simulation isthat they allow us to take intoaccount the time-varying nature ofvolatility. With simple historicalsimulation, we do not necessarilyknow what type of regime existedwhen those simulated resultsoccurred. An event might havehappened in a low-volatilityregime, and the volatility could geta lot worse. I favor methods thatincorporate the time-varyingnature of volatility.

Question: How do you dealwith changes in the composition ofa benchmark?

Longerstaey: The movingbenchmark is just as difficult todeal with as the benchmark forwhich you do not know thecomposition. One of the things thatwe are doing for our own market­ing people is creating categories ofbenchmarks: the ones that we like,the ones that we can tolerate, andthe ones that we do not want to use.Volatility of composition (or froma positive perspective, transparen­cy of construction and content) is akey factor in determining which ofthe three categories a benchmarkfalls in. Interestingly, most of theopposition to certain benchmarkscomes not from the risk manage­ment group but from portfoliomanagers or from the performancemeasurement group, whose livesare directly complicated by thesedifficult benchmarks.

60 ©Association for Investment Management and Research

Practical Issues in Choosing and Applying Risk Management Tools

Question: In backtesting, weassume that portfolios do notchange during the measurementperiod, but portfolio managers doadjust their portfolios. How do youhandle that problem?

Longerstaey: Actually, youdon't get this problem if you usehigh-frequency returns (i.e., dailyor weekly). Another way ofaddressing this problem is to look

at risk and performance in constantportfolios. The issue in this case isthat you may have to calculatereturns on positions you've neverheld since the positions wereunwound over the evaluationhorizon, which may be more costlythan moving your organization tohigher frequency data.

Also, with regard to usingtracking error in another fashion,we are contemplating creating two

risk-adjusted performance mea­sures: one defined as performancedivided by realized tracking errorand another defined as perfor­mance divided by anticipatedtracking error. The ratio betweenthese two performance ratioswould be a measureof the portfoliomanager's efficiency at convertingpotentially higher risk into lowerrealized volatility.

©Association for Investment Management and Research 61

How Risk Management Can BenefitPortfolio ManagersMichelle McCarthyRisk Product ManagerIQ Financial Systems, tnc,'

Using value at risk to analyze portfolio risk may appear to be inaccurate and to presentyet another constraint on portfolio managers. But VAR,which measures an investment'spotential loss exposure over a specified time period at a given confidence level, can helpsenior managers in investment firms practice unified and disciplined risk management,giving investors more-reliable results and permitting portfolio managers to use a lessrestricted range of investment instruments.

R isk measurements help senior managers atinvestment firms supervise portfolio managers

and help clients monitor the mix and concentrationof risks in their portfolios. Although individual port­folio managers may not see the benefits of risk man­agement, it does provide genuine benefits to thisgroup as well. Part of the"disconnect" perhaps liesin different notions of what constitutes risk itself andthus how risk can, or should, be managed. This pre~

sentation defines risk and risk management for aninvestment firm, reviews the background of value atrisk and describes the process of adopting VAR forinvestment portfolios, and discusses the benefits,criticisms, and limitations of VARin a portfolio man­agement context.

Defining RiskRisk for an investment management firm can beviewed from three perspectives: absolute versus rel­ative risk, fund-specific risk versus risk among agroup of funds, and surprise losses.

Absolute versus Relative Risk. Risk can bethought of in an absolute sense-risk that the assetslose more money than the person who owns theassets thought possible. Such absolute losses canoccur because of market risk factors (the usual focusof VAR methodology), factors specific to an issuer,and operational problems (ranging from fraud to notprocessing an order on time).

1Ms. McCarthy is now a managing director at Deutsche Bank.

62

Risk can also be thought of in a relative sense­underperforming the stated intention of the fund, ormore likely a specified benchmark, by an amountgreater than the person who owns the assets thoughtpossible.

If a client has given an investment firm fundswith the intention of outperforming a particularbenchmark, relative risk is the more relevant riskmeasure for those funds.

Fund-Specific Risk. Investment firms some­times apply risk measures across the firm to makesure that the aggregate position of all the funds is nottoo long or too short. This approach, I argue, is lessuseful and less justifiable than looking at the risk ofeach individual fund. Pooling together all the funds,however, may help an investment firm monitorwhether its fee income could drop because all itsfunds are concentrated in the equity markets, forinstance, making it vulnerable to an equity crash.

I believe that risk management in an investmentfirm should look for unacceptably large potentiallosses fund-by-fund, as opposed to across all thefunds, because all the funds are not all one person'smoney. Thus, risk management should evaluate eachfund relative to the constraints and desires of theinvestor. This approach measures the risk of misexe­cuting fiduciary duties or losing customer satisfactionrather than the risk of reduced fee income because ofmarket fluctuations.

Surprise Losses. Risk can also be viewed in thecontext of unanticipated, or surprise, losses. Often,

©Association for Investment Management and Research

when surprise losses happen, certain culprits can beidentified. Sometimes the management informationsystem, particularly if it is based on financial accounts,misses something important. Financial accounts donot display usefully such key risk factors as portfolioduration, currency impact, and derivative exposure.So, management information based on financialaccounts will miss, among others, surprises resultingfrom duration risk, currency risk, and derivative risk.If a senior manager or investment committee usesonly categories that appear on a balance sheet tomonitor how clients' money is being invested, themanager will miss a great portion of the actual risk.

Investment guidelines tackle some risks that donot appear on a balance sheet, but they can be easilyoutstripped by changes in the mix of products avail­able in the capital markets. If the guidelines try tospecify what asset classes or what long or short posi­tions are or are not allowed, the guidelines can easilybecome extremely complex and may not control riskat all. In multicurrency, multiasset funds, investmentguidelines cannot do the trick. Investment guidelinesthat are meant to keep funds safe cannot accommo­date all the things happening in a fund, and thussurprises can occur.

Surprises are also likely to happen when themanager and client do not discuss how much risk isallowed in pursuit of return. If they discuss whatpotential outperformance may occur, then the poten­tial underperformance, which is caused by the samerisks that allow for outperformance, must be dis­cussed as well. VAR attempts to monitor that poten­tial underperformance over time, to help firmsensure that it remains at an acceptable level.

Defining Risk ManagementFor too many investment firms, risk managementmeans "derivatives." Furthermore, when the discus­sion broadens beyond derivatives to incorporate allthe instruments in a fund, confusion often arisesbetween two kinds of risk management: the offenseand the defense.

Offense. Portfolio managers may use risk mea­surement and optimization techniques while seekingto add return to the portfolio. When a portfolio man­ager makes choices to buy, sell, or hedge--choicesbased on an analysis of the risk-return potential of theportfolio-those choices are often based on risk fore­casts that are grounded in history. The manager may,however, forecast that the future will be entirely dif­ferent from history and invest accordingly. Choosingassets based on a model, perhaps changing the modelbased on a belief that the future will be different fromthe past, is part of the "offense" of risk management.

©Association for Investment Management and Research

How Risk Management Can Benefit Portfolio Managers

Defense. Risk management used defensivelyrefers to supervisors looking at a portfolio to see if thelevel of risk is acceptable. For example, oversightbodies within investment management organiza­tions, such as investment committees, or plansponsors might measure the risks in the portfoliosmanaged on their behalf to verify that they arecomfortable with the risks being taken. In these cases,amending the historical data and embedding fore­casts in the models are rare; one tenet of defensiverisk measurement and management is that managersshould not be amending historical data except in aconservative direction. VAR, for the most part, isused as defense in risk management.

VAR BackgroundVAR is defined as the potential change in value, orpotential loss, of a portfolio over some time horizonat some confidence interval (e.g., how much the fundcould lose in the next week with 95 percent confi­dence, how much the fund could lose with respect toits benchmark in the next quarter at 99 percent confi­dence). A loss at 99 percent confidence means that ifthe model does its job correctly, the portfolio willsuffer a worse loss no more than 1 percent of the time.

VAR uses historical data to quantify how mucha portfolio might lose, given the assets the portfoliocurrently holds. The key data that VAR uses to helpdecide whether a fund is risky are the volatility of theassets and the correlations between the assets. Thatstatement should not be surprising because VAR isgrounded in modern portfolio theory and is not verydifferent from risk measures that investment manag­ers have been using for many years.

In the 1980s,banks began to adapt modem port­folio theory, thus creating VAR, mainly because therules they had been using to manage their portfolioswere not working. When they used guidelines thatsimply indicated how many bonds and futures to buy,they were outstripped by the complexity of portfolios.When they tried to look at duration sensitivities, theywere stymied by arbitrage portfolios; they could notdecide which long-short portfolio was truly risklessand which one was not. VAR gives banks the abilityto analyze the risk exposures of their increasinglycomplex portfolios, and banks make great use of VARtoday, not the least because banking regulation hasadopted VAR as a popular method of assessing mar­ket risk capital requirements.

In many aspects, banks are different from mostinvestment firms, and VAR could not have beenapplied to the latter without significant adaptation.Banks, for instance, tend to be more involved withfixed-income and foreign exchange exposures andhave much lower equity exposures than investment

63

Risk Management: Principles and Practices

firms. Banks also have a need to measure the worstcase loss because their regulators want to make surethe banks set aside enough capital for that worst casescenario. Therefore, much of the VAR theory andapplication focuses on quantifying the worst caseloss. Finally, banks tend to be dealers in options andhave a large number of nonlinear exposures, whichrequire a great deal of refinement in VAR measure­ment. Banks' concerns are often driven by the heavyamount of nonlinear product in their portfolios andthe fact that they are option buyers and sellers,requiring banks to run hedged option portfolios.

So, for VAR to work effectively for asset manag­ers, several changes have to be made. First, VAR mustlook at risk not only in the absolute but also versus abenchmark (relative risk). Second, banks tend toexpress VAR in terms of absolute dollars; percent ofnet asset value is a much more helpful display forinvestors because it compares neatly with perfor­mance reporting. Banks cannot meaningfully expressVAR in this way because so many of their portfoliosare long-short and, therefore, have tiny net asset val­ues, even though they have a large amount of VAR,which tends to make percentage expressions infinitelylarge-and not very helpful. Dollar-based measuresare similarly unhelpful for investors.

A third adaptation for asset managers is to use alower confidence interval for VAR than a bank wouldtypically use. In the absence of regulatory capitalrequirements and option use, imposing a high confi­dence interval does not yield extra information, andusing a lower confidence interval means that themanager can better test that the model is a good one.If the manager runs a 1 standard deviation VARmodel, the manager can get many more data pointsto confirm whether or not the model is working. Thenumber will also tie in well with managers' experi­ences: A manager can more easily judge whether aloss of 8 percent versus a benchmark is too heavy tosustain in a normal year (84.5 percent/1 standarddeviation confidence interval) than whether a loss of18.64 percent versus the same benchmark is tooheavy to sustain 1 year out of 100 (99 percent/2.33standard deviations). The fund composition is thesame in both cases, but given that most people'scareers are shorter than a century, the first questionis easier to answer than the second.

Fourth, VAR for investment portfolios requires astronger focus on equities. In most well-documentedVAR models in the public arena for banks, equitiesare treated as benchmarks, which does not help assetmanagers determine the extent to which their equityfunds might fail to track their benchmarks. Equitiescan be brought into VAR as single stocks, which isvery data intensive, or aggregated into industries orother relevant subsectors.

64

A final adaptation that increases VAR's effec­tiveness for asset managers is to incorporate the cli­ents into the process. In this approach, clients firstcreate a benchmark asset allocation and compare thatbenchmark with their liabilities to make sure they arecomfortable. They can then delegate risk to their assetmanagers. They assign a benchmark to their fundmanagers and further clarify how much they want tooutperform that benchmark and what potentialunderperformance they find acceptable in pursuit ofthe target outperformance. This process clearlydefines for the asset management firm what it shouldbe monitoring to be a good fiduciary and to avoidclient dissatisfaction.

Adopting VARAn investment firm contemplating adopting VARhas several tasks to accomplish: understanding thepurposes of VAR, taking an approach to implement­ing VAR, dealing with special cases, measuring theperformance of VAR, and recognizing the benefitsand limitations of VAK

Purposes. VAR has two primary purposes forrisk management of investment portfolios. First, VARmeasurements allow comparisons of risks amongasset classes and funds. VAR numbers are like havinga sensible set of financial accounts that help highlightthe role of risks in a fund. VAR is not a "magic bullet,"but it can be the beginning of an analysis based oncomparability among all funds.

Second, VAR allows for the regular monitoringof risk to see how a fund's risk exposure has changedand to see whether that change is acceptable. Conse­quently, VAR allows unacceptable risk to be changedbefore that risk becomes crystallized as a loss.

Approach. When using VAR for risk manage­ment of investment funds, the investment manage­ment firm must quantify for each portfolio the levelof potential underperformance that is unacceptablyrisky compared with a benchmark (i.e., trackingerror). This number becomes the "risk guideline" or"threshold" for that fund. For hedge funds and fundsfor which a benchmark is not relevant, the managermust determine how much absolute risk is unaccept­ably risky in order to determine the risk guideline.

The investment firm must measure VAR for theportfolio periodically, either in absolute terms orwith respect to the benchmark, and when the poten­tialloss exceeds the investment firm's risk guidelinefor that fund, then the manager must take someaction to get back within the comfort zone. For exam­ple, suppose a manager goes 100 percent into cashusing futures-a change that may not be explicitly

©Association for Investment Management and Research

covered by investment guidelines. VAR will warnwhen a portfolio manager has gone too far into cash;the tracking error with respect to the benchmark willincrease drastically. When such a move is brought tothe attention of the senior managers or investmentcommittee of the investment firm, these senior man­agers will have to decide whether being that muchout of the market is a good idea. Of course, the fundmanager probably has made that move because he orshe believed something terrible was about to happen.But if the manager knows with great certainty whatwill happen tomorrow, why not use the leverage togo short the market? The penalty of being 100percentin cash is that the manager could miss that potentialuptick in the market that everybody else catches andseriously underperform the benchmark.

Limits need to be set ahead of time to helpdetermine how much risk is too much for anystrategy. Absolute risk limits may be required inaddition to, or instead of, risk limits versus abenchmark (tracking error). In that regard, however,VAR does not replace the use of investment guide­lines. Many guidelines are still useful for makingsure that the portfolio or fund stays within specificissuer concentration limits, liquidity constraints, andother specified exposures. Without such guidelines,VAR might show that a portfolio looks terrific, butin reality, the portfolio may be overconcentrated inone issue and lose too much money on that issue orit may have inadequate liquidity.

Implementation. Implementing VAR as part ofan investment management risk system requires twopieces of information: the instruments comprisingeach benchmark and the instruments comprising eachfund. The fund contents and the benchmark contentsmust be broken down into risk factors, which in effectare pricing sensitivities-s-such as the sensitivity of agiven note to a 1basis point increase at different pointsof the yield curve or a foreign exchange forward'ssensitivity to the change in the relevant foreignexchange rate and changes in the yield curves of bothcurrencies. These sensitivities (also known as "expo­sures" or "positions") are brought into the VARengine, and VAR measures, both absolute and rela-

How Risk Management Can Benefit Portfolio Managers

tive, are produced. Table 1 shows possible VAR mea­sures for a one-year holding period and a 1 standarddeviation (84.5 percent) confidence level for fourfunds: an active U.S. equity fund, an internationalequity index fund, a money market fund, and a hedgefund. The VAR engine indicates that the active U.S.equity fund might lose 15 percent of its absolute valuebut only 5 percent with respect to its benchmark-theS&P 500 Index-because the mix of assets in the fundis different from those in the benchmark. Similarly, theinternational equity fund could lose 20 percent in thatone year in absolute terms and 8 percent with respectto its benchmark-the Morgan Stanley Capital Inter­national Europe/Australasia/Far East Index (MSCIEAFE). The money market fund, as expected, has atiny VAR in both absolute and relative terms. Thehedge fund has a large VAR in an absolute sense, andbecause the hedge fund's benchmark is T-bills, itsabsolute risk is the same as its relative risk.

The last two columns in Table 1 show the VARrisk thresholds that were set ahead of time. Theinvestment committee might determine these thresh­olds based on how the fund has been marketed or onthe worst loss the fund has suffered; these thresholdsmight be ones explicitly stated by the plan sponsor,or they might be simply common sense. In any case,these numbers represent a standard against whichthe VAR numbers can be compared. For example, theactive Ll.S. equity fund should not be able to under­perform by more than 4 percent (relative terms). Theinternational equity index fund has both an absoluteand a relative risk limit; the money market fund hasonly a relative risk measurement; and the hedge fundhas only an absolute risk measurement.

The VAR engine shows that the active u.s. equityfund's relative risk is higher than the threshold. Whatthe manager does at this point depends on the way hisor her firm works. In some firms, the investment com­mittee looks at those VAR numbers that are over thethreshold and decides whether or not being over thethreshold is acceptable. Others require the manager toreduce over- or underweight positions immediately inorder to bring the VAR figure under the threshold.

Table 1. Fund VAR Measures (Absolute and Relative) and Risk Thresholds

Fund/Benchmark

Fund YAR Measures'

Absolute Relative

Risk Thresholds

Absolute Relative

Active us. equity/S&P 500 15.0% 5.0% 4.0%International equity index fund/MSCI EAFE 20.0 8.0 23.0% 10.0Money market fund/Index 0.1 0.1 0.13Hedge fund/T-bills 28.0 28.0 35.0

'YAR measures specified for one-year holding period and 1 standard deviation (84.5percent)confidence level.

©Association for Investment Management and Research 65

Risk Management: Principles and Practices

Implementing a risk management system suchas that envisioned in Table 1 is not trivial. Breakingout all the data on the funds and benchmarks into riskfactors is difficult. The system also needs a VARengine and historical data with which to compare theVAR numbers. For every fixed-income and deriva­tive product, the system needs valuation models tobreak these products down into risk factors. Finally,data (often from disparate systems) must be consoli­dated and converted.

A regular reexamination of what risk thresholdsare acceptable is also part of the system, and havingclients who are like-minded and agree with the risklevels is very helpful. In addition, scenario analysisshould be used to supplement the VAR numbers.Once portfolios have been broken down into riskfactors, running them through a historical scenario,such as the crash of 1987, is relatively simple to do.The only portfolio that would have been bulletproofagainst every crisis that occurred in the past 20 yearsis T-bills, but being immune to all potential crisescannot be the goal of this analysis, because doing sowould entirely preclude any risk taking and anychance of gain above the risk-free rate. If the invest­ment firm does.not believe that history will repeatitself, it can run the portfolio through a simulatedscenario. Even positions that look acceptable in theVAR framework may not pass historical or simulatedstress testing, in which case the manager might actu­ally (and for good reason) construct positions that aresuboptimal in a VAR sense.

One important issue for most investment firmsis the new product review process. The managerneeds to make sure that the VAR system will capturethe data and all the risks inherent in new products.For example, if a manager has taken on prepaymentrisk for the first time in the fund, the system must beable to capture that risk.

Liquidity and credit screens are important toensure that a manager does not own too much of oneissue in one market. If a firm measures possible riskby looking at the historical volatility of price move­ments in an asset when normal-sized lots are beingtraded but the manager owns 90 percent of the mar­ket in that asset, the manager will not experience themeasured volatility the day he or she goes to trade.Firms should be sure their positions are not oversizedwith respect to average daily trading volume; if theyare, the firms must acknowledge this fact and adjustfor any oversized positions by increasing their VARmeasures accordingly.

Special Cases. Hedge funds and emergingmar­ket funds pose special challenges to VAR adoption.

• Hedge funds. Sometimes investors want toroll their hedge funds into their overall portfolio VARmeasurements, but unless they have access to portfo-

66

lio holdings of the hedge funds, doing this analysis ispointless. Compared with its use for traded invest­ments, VAR is weaker for the analysis of nontradedinvestments-for instance, venture capital invest­ments or real estate partnerships. If no reliable, pub­licly available periodic price data exist for aninvestment, then it is difficult (if not impossible) tobuild portfolio proxies, which VAR requires.

VAR is useful, however, for hedge funds thatdeal in tradeable securities, whether they use long­short or other types of strategies. If an asset class canbe neatly matched to benchmarks and financialinstruments, VAR is applicable, no matter how com­plex the strategy. Long-short strategies, however, dorequire much more refined VAR analysis than long­only strategies. If a manager simply buys assets andcompares them with a benchmark, the managerneeds only a modestly refined analytical system. Butif the manager is taking relative risk, such as with along-short strategy, the manager needs a high stan­dard of proof and a high degree of refinement in hisor her VAR model.

For example, suppose the historical data for aportfolio VAR model include only J-year, 3-year, andlO-year data for French bonds, rather than the entireFrench yield curve. The portfolio adopts a strategythat is long $1 billion the 3-year and short $775 mil­lion the 4-year French government bonds and makesa significant amount of money with that strategy. Ifthe bonds are duration weighted, the unadjustedVAR model may collapse them both into a 3-yearcategory so that the portfolio looks to be long $1billion duration equivalent of the 3-year bonds andshort $1 billion duration equivalent of the 3-yearbonds (which is the $775 million 4-year positionduration adjusted into a 3-year bond equivalent),thus showing zero risk yet a high return.

With more-detailed historical data on Frenchbonds (l-year, 2-year, 3-year,4-year, 5-year, etc.), theVAR analysis would show that the portfolio is actu­ally $1 billion long the 3-year and $775 million shortthe 4-year bond. If those two bonds are not 100 per­cent correlated, VAR will show some risk coming outof that analysis. That risk was missing before becausethe VAR modeling was too crude for the actual strat­egy being pursued. So, without explicit categories forthe two legs of a very important long-short strategy,that strategy will show zero risk, which is, of course,misleading.

• Emerging markets. Emerging market invest­ments also pose challenges for VAR analysis. Theproblem of illiquidity is again crucial; standarddeviation is a less effective measure for typicallyilliquid markets and for markets in which themanager is overconcentrated. If an asset normallytrades infrequently and/or in small sizes, then any

©Association for Investment Management and Research

time a manager makes a normal-sized trade in thatasset, that trade itself will raise the standard devia­tion. If the manager happens to be overconcentratedin that illiquid market, the effect is that much morepronounced. So, standard deviations are suspect inthe case of illiquid markets, which obviously includeemerging markets, and VAR is thus weaker for thosewho invest in such markets.

In addition, illiquid markets have "fat tails,"which means that rare events are more common thanwhat is estimated by statistics built around a normaldistribution. Illiquid markets are characterized bylong periods of boredom punctuated by short periodsof terror-not a smooth distribution of price changes.Furthermore, in many of these markets, finding his­torical data to build VAR analysis is difficult. Forexample, when investors first moved into Russia, nohistorical market data were available, and yet inves­tors trusted analyses that required quantification.Finally, in these markets, VAR and VAR-like modelsmay not suitably capture the characteristics of rapidlyevolving financing instruments, such as convertibles.Models typically used to price these instruments andbreak them down into risk factors have been shownto be unreliable in the less liquid markets.

II Adjustments. These difficulties have led VARusers to adjust their models in various ways. Somemanagers, for instance, create a more fat-tailed distri­bution for their emerging market investments. Theymodel the normal behavior statistically and then saythat a 99 percent event for that market is three or fourtimes the standard deviation.

Most managers prefer the historical-simulationVAR model over those models that rely on volatilitiesand correlations. Historical simulation does notmodel high confidence intervals by extrapolating outfrom the standard deviations of market movements,making this model preferable for illiquid markets. Ittends to more accurately reflect the "fat tails" thanother approaches.

Some managers keep the VAR measure as is butsupplement it with extra stress tests from those mar­kets. By doing so, they are trying to indicate that thepossibility exists that a much larger event could hap­pen than what would ever be predicted.

Some managers add an arbitrary"charge" to theirVAR estimates for certain holdings or markets. Forexample, the standard deviation of a market may be15 percent, but the manager might think the "true"volatility of that market is higher than 15percent. Themanager may arbitrarily add a charge to the VARengine reflecting the extra volatility of the positions inthis market, in which the charge, when added to thebase 15 percent volatility, will never show a total vol­atility in that market of greater than 100percent. When

©Association for Investment Management and Research

HowRiskManagement Can Benefit Portfolio Managers

managers first started trading in Russian equities, theyfrequently charged 100percent VAR for their Russianequity positions. This process is not very scientific, butit does attempt to recognize the special nature of suchmarkets. Another similarly arbitrary adjustment thatmanagers sometimes make is with respect to individ­ually modeled instruments. Convertible or high-yieldbonds in emerging market countries may be treated as100 percent equity, for example, instead of beingtreated as partially equity, partially fixed income. Suchtreatment may add too much conservatism to a VARmodel during good times but just about the rightamount during bad times.

Finally, some managers increase the holdingperiod assumption for illiquid markets. If they areusing a one quarter and a 1 standard deviation mea­sure for their more "normal" funds, they might use alonger period for their emerging market funds toreflect the decreased ability to close out these posi­tions compared with their more liquid positions.

Performance Feedback. Backtesting is a pro­cess that attempts to determine if all of this risk analy­sis has done any good. The manager predicts howmuch the fund might lose with respect to the bench­mark every day or every week and then records theactual result at the end of that period. Figure 1 showshow well this VAR model predicted the actual lossesover a one-week time frame. The squares represent thepredictions made at the beginning of the week, and thedots represent the actual results measured at the endof the week. If this model used a 99percent confidenceinterval, 99 percent of the dots should be above theVAR predictions and no more than 1 percent of thesample should be below the predictions. If the actual

Figure 1. Backtesting: Actual Gains and Lossesversus VAR Predictions Using WeeklyData

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67

RiskManagement: Principles and Practices

gains are below the predicted gains more than 1 per­cent of the time, then this model requires amendment.The manager might have a lot of exposure to illiquidmarkets, or the manager might have an overconcen­tration in a single issue, both of which would distortthe model. The manager can continue tweaking themodel, or if the manager is completely in venturecapital or real estate, he or she may decide to discon­tinue using the model or to use different proxies forthe assets in the portfolio.

With backtesting, the manager needs to makereasonably frequent measures of VAR and portfolioperformance. Backtesting does not work on a quar­terly basis; a weeklybasis can even be a stretchbecauseweekly testing misses intraperiod rebalancing thatmay be the source of profit and loss. With weeklytesting, the manager might find that the predicted andactual numbers are very different from one another.

Comparison with Other Measures. One impor­tant benefit of VAR, especially compared with asset­specific investment guidelines, is that VAR is notlimited to one asset class. An equity fund's guidelinesmight specify that its beta should not be higher thanx, and a fixed-income fund's guidelines might specifythat its duration should not be longer than y. If thefixed-income fund goes one month longer in dura­tion than y and the equity fund goes 0.1 higher in betathan x, which is riskier? Those two statistics are notcomparable if one wants to look at a fund complex tosee which managers are too close to their risk toler­ance and which are comfortably within their risktolerance. When using only beta and duration, howwould someone look at the risk of a multicurrencyand multiasset fund or of a balanced fund that hasfixed income and equities and perhaps even interna­tional assets? Analyzing the risk of such portfolios isvery difficult with only beta and duration, but verypossible with VAR.

Standard deviation of a fund's past results iscomparable among asset classes, but standard devi­ation is not an early warning of whether a fund hassuddenly changed its composition. Because standarddeviation is historical in nature, it will show how thefund manager behaved in the past. But if a managerwants to see if a new position might exceed a client'srisk tolerance, standard deviation will not helpbecause it is backward looking; it does not use thecurrent set of assets. VAR, however, uses the currentset of assets to generate the risk measure.

Unlike investment guidelines, VAR does not relyon the names of assets in order to categorize them.For equities, using VAR is not very different fromusing investment guidelines. But for fixed-incomeand derivative instruments, an especially importantcharacteristic of VAR is that it does not look at the

68

name of an asset but, rather, runs each asset througha pricing model and identifies each of its pricingvariables individually. For example, structured noteswere able to get into portfolios because they obeyedthe letter, although not the spirit, of the law. Supposea manager had a one-year AAA note suitable for amoney market fund, but its performance was actuallylinked through a formula in its coupon payment tothe behavior of a 30-year CCC note. The one-yearAAA note fit the guidelines, but it had the pricevolatility of a 3D-year CCC note. VAR models eachinstrument in a pricing model and identifies its sep­arate pricing variables. If VAR had been used withthis AAA note, it would have shown the note clearlyas a 3D-year CCC note.

Benefits to Portfolio Managers. VAR has thepotential to allow portfolio managers greater free­dom. Compared with using only investment guide­lines to control risk, VAR is a better system for fundsthat may need to use different instruments or mayneed to have a currency-hedging strategy. VAR is atargeted way to express the role of leverage; it cap­tures leverage by measuring how much loss couldoccur in the geared assets and how much loss couldoccur from the difference between assets that wereshorted versus those that were bought. So, managerswho want to use creative strategies should view VARfavorably. I do not mean to suggest that managersshould have no investment guidelines but, rather,that judicious use of VAR can avoid a manager'sbeing unable to use strategies that are sensible butdifficult to address in investment guidelines. Numer­ous cases now exist in which a client agrees on VARlimits for funds that are going to use leverage orderivatives, and the client monitors the manager'suse of these instruments through VAR reporting toconfirm that the risk suits his or her tolerance. Port­folio managers who are prevented from using usefulinstruments because they fall into categories prohib­ited by the investment guidelines could add value byagreeing with the client to adopt VAR monitoring inlieu of certain kinds of guidelines and thus be able touse a wider range of instruments. So, some of theinvestment guidelines and constraints in place couldbe relaxed if clients become more comfortable andhave more time and experience with VAR as analternative control tool.

VAR can be used across different portfolios as asupervisory tool because it applies the same measureacross every fund, whether the fund is passive,active, equity, fixed income, balanced, or a singleasset. VAR also provides a language for allocatingresponsibility more effectively, especially if a clientexplicitly states what potential underperformance isacceptable in the pursuit of gain. As a framework,

©Associ~tion for Investment Management and Research

VAR clearly states that asset allocation is the client'sresponsibility and that performance versus a bench­mark is the fund manager's job, in which the manageris responsible for staying within the tracking-errorboundary established by the VAR risk threshold(rather than trying to manage absolute risk).

Using VAR can also impart a competitive advan­tage. After a year such as 1998, when some fundssustained significant losses, clients want to see whatframework a manager has in place to avoid havingsurprises and losing money. VAR is a way to avoidsome of the surprises that would be buried in otherkinds of reporting.

Criticisms and Limitations. VAR is frequentlysubject to criticism, much of which can be addressed,and has real limitations, which must be recognizedwhen a firm chooses to adopt VAR measurement.

• Criticisms. Byusing VAR,a manager is specif­ically acknowledging potential investment loss orunderperformance. Managers at banks frequently dis­cuss their potential losses; they set capital aside forlosses and respond to regulators who receive regularreporting of a bank's loss potential. The investmentmanagement industry, however, does not use theword "loss" (the "L" word) very often. Clients shouldexplicitly agree that a loss of a certain amount isacceptable or possible in the pursuit of gain, which isnot common in the investment industry and which isrequired for a proper acknowledgment of who haswhat authority and what responsibility. Clients mustrecognize that they are signing up for a potential lossas they pursue outperformance. If a client cannotacknowledge a potential loss, then no potential loss isever acceptable.

Using a single measure to evaluate all managersmeans that they are all being measured against thesame time horizon. No matter whether one manager'sstrategy relies on day trading or another manager'sstrategy relies on a five-year holding horizon, they areboth being measured against the same time horizon,be it one day, one quarter, or one year. This use of afixed time horizon is one reason why VAR is oftenunpopular. When faced with this fixed time horizon,managers sometimes say, "I would not lose that muchin a quarter. I would day trade out of it" or "A quarterdoes not matter in my fund; I have a five-year hori­zon." The problem with this sort of objection is that afund does have unacceptable annual, quarterly, ormonthly performance numbers; they are, in fact, allcompared with the same standard at regular intervals.Ifa client is going to look at performance numbers fora time period less than a full market cycle, then mea­suring risk to the same time horizon makes sense. If aclient is very disciplined and never reacts to a quar­terly performance number, then the client will be very

©Association for InvestmentManagementand Research

How Risk Management Can Benefit Portfolio Managers

disciplined and never react to a quarterly risk number.The client will set enormous risk thresholds. Investorsdo not fall asleep for five years and then look atperformance at the end of five years; they look atreturns intraperiod and occasionally instigatechanges based on intraperiod performance. Similarly,managers' risk numbers can be compared intraperiod.

The snapshot style of VARmeasurement does nottake into account the dynamism of active strategies.VAR takes today's portfolio, assumes the managerfalls asleep for the holding period (say one quarter),and predicts the possible loss in a quarter. Use of thissnapshot approach is a genuine criticism. To test thevalidity of this criticism, one could measure over timethe extent to which VAR failed to track the actualperformance that managers sustained. If the trackingerror is marked and consistent, then this dynamismreally matters. IfVAR actually did a good job predict­ing actual results, then the dynamism matters less.

Defensive risk management should be indepen­dent; it cannot rely on managers' own pictures oftheir risk, else it is not a double check. It will alwaysbe cruder than the tools managers use to monitor andcraft their own strategies. It must be; otherwise, itwould involve overly costly duplication of effort.VAR analysis always simplifies complex strategies~

always boils things down to broader categories-s-andthus will always be subject to criticism by managersbecause they are aware of its shortcomings comparedwith their own modeling. Additionally, the"offense"will never numbly use historical data alone to cometo conclusions about the portfolio, as VAR measuresoften do. It is almost a requirement of portfolio man­agement to believe the future will be different fromthe past, else investing is a zero-sum game. Managerswill amend models based on historical data to reflecttheir unique insights of the future or use no historicaldata at all. This approach is exactly what should bedone to earn good returns but should not be dupli­cated in the "defense" system. The answer to mostcriticisms of VAR comes in the backtest when one cansee how well the model predicted the results. If VARdoes a good enough job, then it does not need a heavyand highly layered infrastructure.

In general, VAR is criticized because it is back­ward looking. Criticizing a backward-looking modelis easy. The model everyone wants has the futuredata set in it. And by comparison, the backward dataset always looks inadequate, but it is the only oneavailable. History will always take an unexpectedtum from time to time, but that fact does not defeatthe value of taking a disciplined look at how thecurrent portfolio would have gone through history.History predicts a great deal of portfolio movement,even if it does not predict it all.

69

Risk Management: Principles and Practices

The model is supposed to be wrong a certainpercent of the time (100 minus the confidence inter­val), and it may be wrong in grand style on thoseoccasions. Instead of focusing on whether VAR is aperfect prediction of potential loss, it is more usefulto observe that VAR can help highlight the fact thata fund has become riskier from one day to the nextbecause of a change in its assets. VAR may not quan­tify the actual perfect amount of loss that could besustained, but it helps highlight when, because of achange of positions, the risk has gone up. That abilityto highlight change is of greater value than the actualperfection of the forecast and allows the manager totrim the positions before the VAR figure, or a largernumber, is realized.

Perhaps the main reason for VAR's unpopularityis that it adds another constraint in a highly con­strained industry. Asset managers already have todeal with various legal constraints and investmentguidelines, and VARpresents another set of activitiesthat could constrain a manager's freedom and chanceto add alpha to a fund. As noted previously, the silverlining comes if VAR is allowed to substitute for lessuseful guidelines, thereby removing bad constraintsand introducing more logical rules.

• Limitations. Risk measurement in generaldoes not prevent losses altogether, and VAR is nodifferent. When a firm loses money, the explanationis not necessarily that its VAR system failed. Eventhough VAR users are quantifying risk every day,they must keep in mind that the potential loss mea­sured by this technique could actually occur.

VAR also does not decide what risk threshold isacceptable: that decision must be made by manage­ment (e.g., the plan sponsor or the investment com­mittee). VAR measures how much risk is in a fund,and management must determine when to start react­ing to that exposure by making changes in the fund.

70

Losses within the specified confidence intervaldo not constitute model failure. In other words, at aconfidence level of 99 percent, a loss 1 percent of thetime is not an indication of model failure. If that losshappened 10 percent of the time, then the modelwould have failed to predict losses. In addition, if theuser does not follow the rule of making only conser­vative adjustments to the model, then the user cannotclaim model failure. Finally, if management does notimplement any thresholds beyond which actionwould be taken and an unacceptable amount ofmoney is lost, management cannot blame the model.Therefore, when evaluating an instance in which amodel was supposed to have failed, one must look tosee if the loss occurred within the confidence interval,if adjustments were made to the model, and if anylimits whatsoever existed. Ifmanagement had not setany limits, for example, then the loss cannot beblamed on model failure.

ConclusionVARis a disciplined, unified way to look at the risk inan investment portfolio. Its value is clear to seniormanagers in investment firms and to plan sponsors.It allows them to compare portfolio managers and toflag situations that may require attention. From aportfolio manager's viewpoint, VAR can be anotherlayer of constraint, but VAR monitoring can actuallypermit the removal of some constraints that are placedon portfolio managers, particularly if they want to usestrategies that involve instruments that normally can­not be accommodated by investment guidelines. If afirm's clients agree with the VAR system thresholds,there will be less room for misinterpretation and thequestion of who is responsible for what portion of thefiduciary decisions will be clarified.

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How RiskManagement CanBenefit Portfolio Managers

Question and Answer SessionMichelle McCarthy

Question: Once you have anapproved risk process, how do youpermit exceptions?

McCarthy: VAR analysis is dif­ferent in this regard from invest­ment guidelines. For someinvestment firms, any exception toa guideline triggers an automaticaction. When I was in the invest­ment management group at Bank­ers Trust Company, when we firstimplemented the system, we triedto be a little slower to react to VARmonitoring because we needed tounderstand what the model told uscompared with our business judg­ment. Ifyou have just adopted a setof thresholds and you have nottested them in practice, you need todecide whether VAR is soundingan alarm too often or whether therisk is normal. VAR provides achance for human judgment andmanagement to come into play,rather than an automatic actionbeing taken.

Even once you have approvedand adopted the model, it is con­stantly evolving. You might addthings to improve the risk mea­sures. You may see that your riskmeasurement system overstatesthe risk of a certain portfolio in astrange way and that if you con­tinue limiting the portfolio and for­bidding it to be in that position, itmay not have a chance of gettingany kind of outperformance. Youare continually balancing the needto control with the need to addalpha in a fund.

Question: Do VAR numbersvary among vendors?

McCarthy: If all the vendors usethe same type of VAR model, theirresults should not vary. But if youcompare a Monte Carlo-type VAR

result with a historical-simulation­type VAR result with a parametric­type VAR result, you should notget the same answer. Even if thevendors are using the same type ofmodel, you should check that theyare using the same confidenceinterval and holding period andthe same data history.

Question: Please discuss the im­portance of the time horizon andthe length of the data history.

McCarthy: The most likely thingto happen tomorrow is whathappened yesterday, but such ashort data history (yesterday'sprice changes) has very little to dowith what investment managersare interested in. A longer datahistory, such as three years, makesbacktesting less accurate but cap­tures tail events or crises betterthan a short data history, simplybecause more things happen in alonger period of time.

Some investment managerscriticize the three-year holdingperiod because it does not containa full market cycle. But if you use20 years of data, the backtestresults will be even less accurate inthe near term. You will have olddata and relationships betweenmarkets that do not exist anymore,and you will have limited ability tocalibrate your model and test itsvalidity. With 20 years of data,however, you will have a lot ofmarket crises and tail events thatyou might want to capture.

I believe that having a longdata history is important becauseit will incorporate more marketmoves than those occurring dur­ing the past couple of weeks.Something in the three- to five­year horizon usually capturesenough market excitement to sat-

isfy most people. Clearly, if youuse only the past 100days, you canmiss something.

The bottom line is that nobodyknows which piece of market his­tory best predicts the period thatyou are concerned about in thefuture. The best thing is to stickwith one historical period andbacktest the results of your VARmodel for a period of time. If youare dissatisfied with the backtest,you may want to tinker with thedata history at that point. I thinkthat you should always assumethat if a period has been overlycalm, the future is likely to beworse than predicted, so VARusers who are concerned with thislikelihood will need to be doublysure to couple VAR measurementwith rigorous stress testing andscenario analysis of the portfolio.

Question: If you use a long datahistory, should you decay the data?

McCarthy: Decaying the data(e.g., in 100 days of data the mostrecent 10 days might have 90percent of the weight) has value,but you have to be careful. If youdecay the data, your VAR numberwill not drop abruptly when an oldcrisis disappears out of your dataseries. The decaying techniqueprogressively discounts older datapoints, so the crisis will be weanedout over time. Decaying the datadoes mean, however, that you aremaking less use of that crisis inyour VAR estimate as time goes on.

lt is a judgment call, and myown judgment is that with invest­ment management, we are usuallytalking about long holding peri­ods, so theories that make sense forpredicting the next day or the next10 days are less valid than those forlonger time periods. For invest­ment management applications,

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RiskManagement: Principles and Practices

having a longer data history makessense, and if you refrain fromdecaying or de-emphasizing somedata or generally trying to smooththe data out, you let the recordspeak for itself.

Question: How do you identifywhich security is making theportfolio VAR too high?

McCarthy: Most VAR method­ologies have extra measures toidentify the portions of a portfoliothat are contributing most heavilyto the portfolio's risk. A classicmeasure is called marginal VAR orincremental VAR, which can bemeasured in terms of the bench­mark tracking error. That is, if Ieliminate this stock, this sector, orthis country, incremental or mar­ginal VAR will indicate how muchthe tracking error would bereduced. If you do this analysis,however, for every single asset,every sector, and every country inthe portfolio, you will get informa­tion overkill. Thus, most VARusers try to identify the subcompo­nents that they want to monitorregularly and see how much thosebroader categories contribute tothe overall portfolio risk.

Question: How would youassess a risk management systemthat used only historical priceinformation rather than a VARmethodology?

McCarthy: Such a system canconvey only partial informationabout risk exposures. If a managerknows only the price of a com­pound type of security and doesnot break it up into risk factors, themanager cannot simulate how thatsecurity will behave under differ­ent market scenarios. If the onlydata a manager has on a convert­ible bond are its price and howmany bonds he or she owns, themanager does not know how muchof the bond's performance and riskis equity derived, bond derived, orcurrency derived.

Also, if you ran a firm just byrisk management based on history,you would not bother investing.Risk management assumes a zero­sum game, and it assumes thefuture will be like the past. Historyis a disciplined way of looking atwhat can happen to a portfoliobecause we do not have the futuredata set; however, it is not the onlything that portfolio managersshould have at their disposal. They

should have their knowledge of themarket and their beliefs about howhistory will change. VAR is a wayto make sure that a manager's posi­tions that are based on beliefsabout the future (beliefs that thefuture will be different from thepast) do not have the capability toreally hurt the portfolio if historydoes in fact repeat itself.

Question: Do you recommendusing daily or weekly data collec­tion for measuring actual numbers?

McCarthy: Data collection andmeasurement frequency shouldrelate to your trading frequency.Daily collection makes sense forday traders and financial institu­tions, but daily data are incrediblynoisy. Even if you do not tradeparticularly frequently, however,it does not make sense to look atdata only once a quarter if somemeaningful portfolio changes arelikely to take place in that quarter.Weekly data are a nice compro­mise. Weekly data give moreflexibility than monthly or quar­terly data without having thenoisiness of daily data.

72 ©Association for Investment Management and Research

Risk Analysis: A Geometric ApproachBrian D. Singer, CFAManaging DirectorBrinson Partners, Incorporated

Quantitative methods for risk management should allow investors and portfoliomanagers to look at, and try to manage, risk in new ways. A geometric approach canhelp in displaying the risk characteristics of a portfolio and its benchmark and inassessing the impact of portfolio constraints.

R isk management and quantitative methods aretypically considered to be almost interchange­

able, even to the extent that risk managementrequires or depends on quantitative sophistication.Although a quantitative perspective can certainly beuseful in risk management, too often quantitativemethods and analytical elegance provide the illusionof control over risk. Such approaches make investorsfeel as if they have grasped uncertainty and dealtwith it simply by the act of quantifying it. But risks,by their very nature, are unexpected. So, quantitativemethods should not turn confidence into arrogance;rather, what quantitative methods should do is allowinvestors (and portfolio managers) to look at risk innew ways-to try to manage risk in ways that theypreviously could not do, or were not necessarily com­fortable doing.

This presentation discusses a process that usesEuclidean geometry to visualize risk. Such anapproach is somewhat avant-garde for risk manage­ment and is decidedly quantitative, but the intent isto illustrate a tool that enables quantitative risk man­agers to communicate with nonquantitative portfoliomanagers and nonquantitative clients. Although theapproach applies to any investment horizon, this dis­cussion takes a relatively long-term perspective onrisk-one that is typical of an investment policyperspective-and allows direct analysis of portfoliorisk and portfolio constraints.

Risk Estimation: DataRisk estimation relies on volatility and correlationdata to construct covariance matrixes; one of the keyquestions, of course, is which data?

Historical Data. Risk estimation typicallybegins with the use of historical data-the computa-

©Association for Investment Management and Research

tion of historical volatilities and correlations. Histor­ical data are consistent, easy to obtain, and often easyto compute. A manager, for instance, can compute acovariance matrix very easily with Microsoft Excel.The problem with historical data is that the data arealmost certain to be inappropriate representations ofthe future.

An investor looking at a broad index of the U.S.bond market, such as the Lehman Brothers Aggre­gate Bond Index, would find that the volatility of thatindex was in excess of 10 percent in the late 1970s andearly 1980s. Currently, that same index has a volatil­ity of 4-5 percent. That historical period (late 1970sand early 1980s) was characterized by high and vol­atile inflation, which is not the case now. Thus, thatinvestor would not want, in any forward-lookingsense, to rely on that period as a foundation for his orher risk estimates unless the investor believed, forexample, that the U.S. Federal Reserve Board wasplanning to monetize, or in effect provide an inflationtax for, fiscal policy.

This is a very real investment problem: Supposeat Brinson Partners we are trying to set the invest­ment policy-the normal policy mix-for a pensionplan, an endowment, or a foundation. In thatinstance, the client's time horizon is long term, so wedo not want to know a daily or weekly value at riskestimate. History might not necessarily representwhat we think could happen in the future, but ananalysis of monthly or quarterly data going backseveral decades aids in our understanding of risk invarious economic and market environments.

Granted, a number of advances in statistical meth­odology applied to historical data have occurred: theuse of volatility clustering, the use of generalizedautoregressive conditional heteroscedasticity, and the

73

Risk Management: Principles and Practices

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Figure 1. Visual Representation of Volatilitiesand Correlations from a U.S. DollarPerspective

This ability to manipulate shapes starts in child­hood. Children at a very young age learn to putround pegs in round holes, square pegs in squareholes, and triangular pegs in triangular holes. Theyunderstand and learn to manipulate shapes longbefore they are able to grasp algebra and other math­ematical concepts.

Mark12.0%

cos(a) = P(£/DM) = 0.71

Dollar

Currency RiskAssume that from a U'S. dollar perspective the U.K.pound has a volatility of 12 percent and the Germanmark also has a volatility of 12 percent. The correla­tion between the pound and the mark is 0.71.Although with this information an investor can con­struct a very simple covariance matrix, another wayof looking at the covariance matrix is geometrically,as shown in Figure 1. Volatilities are shown as dis­tances, and correlations are shown as angles. To con­struct Figure 1 from a U.S. dollar perspective, I firstmade a point for the dollar. Because the volatility ofthe mark compared with the dollar is 12 percent, Idrew a line of length 12. That line could be 12 inches,12 centimeters, or 12 kilometers; it does not matter,just 12 units of length. The volatility of the poundagainst the dollar is also 12 percent, so I needed todraw another line of length 12. The question is, whatis the relationship (or the angle) between those twolines? The answer is that the relationship is deter­mined by the correlation, which is 0.71 in this exam­ple; specifically, the cosine of the angle is equal to0.71. The cosine of 45° is 0.71, so I drew the secondline at a 45° angle to the first line. Thus, I haveportrayed the same covariance matrix, but instead of

Note: p is the correlation coefficient.

Forward-Looking Data. Because such regimechanges are possible, forward-looking volatilitiesand correlations can be, although are not always,better representations of the future. That regimechange in New Zealand was quick and identifiable,but historical data would not have predicted it. Thus,having some type of forward-looking perspective, interms of the covariance matrix, is a good idea. Butforward-looking matrixes also have problems, thebiggest one being limitations on human imagination.In a forward-looking sense, people can only incorpo­rate what they imagine, but risks, by their nature, areunexpected. Therefore, it is difficult to incorporatethe appropriate forward-looking events or regimechanges that might affect the covariance matrix.

use of mean reversion for forecasting volatilities. Allof those historical approaches have been beneficial forestimating risk, especially over short horizons, butinvestors are still faced with regime changes-somenotable, some not notable; some identifiable, some notidentifiable-and every regime change decreases therelevance of historical data.

An interesting example comes from NewZealand, which for years suffered from high andvolatile interest rates and, therefore, volatile bondreturns. In an attempt to change that environment,New Zealand altered the charter for its central bank.The New Zealand central bank now provides aninflation target, and if the head of the central bankdoes not meet that target, he or she is fired. NewZealand's inflation volatility is now much lower thanit was in the past.

Geometric Representation. Other importantdifficulties with using a forward-looking perspectiveare achieving consistency and intuition, which iswhere Euclidean geometry comes in. A geometricinterpretation of volatilities and correlations has thepotential to make risk estimation consistent, practi­cal, and more intuitive to understand and communi­cate, especiallybetween quantitative-oriented peopleand non-quantitative-oriented people.

Why take a geometric approach? The mathema-tician Keith Devlin has commented that

mathematicians may be able to express theirthoughts using the language of algebra, but gen­erally, they do not think that way. Even a highlytrained mathematician may find it hard to followa long, algebraic argument. But every single oneof us is able to manipulate mental pictures andshapes with ease. By translating a complicatedproblem into geometry, the mathematician isable to take advantage of this fundamentalhuman capability.

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Risk Analysis

Pound

Portfolio

Mark

·.3.8%

BenchmarkI

(l-l3)uBenchmark

rrBenchmark

~(TBenchmark

<TBmchmark

cos(().) = PPortfolio, Benchmark

Dollar

Note: p is the correlation coefficient.

Kingdom approaches joining the EMU. Figure 2shows what happens if the correlation between thepound and the mark is 0.95, which corresponds to anangle of about 18°: A correlation of 0.95 means thatthe pound must have a volatility of 3.8 from a markperspective. So, compared with Figure 1 (where thecorrelation was 0.71), the volatility dropped from 9.1to 3.8. If we are not comfortable with that change involatility, then we cannot be comfortable with ourcorrelation estimate of 0.95. Notice that if the correla­tion between the pound and the mark were 1.0, theline would essentially become flat, which implies thatthe pound would have no volatility from a markperspective.

(T Porrjo/io

Figure 2. Effect of Correlation Change

Portfolio Risk AnalysisRisk analysis of a portfolio relative to its benchmarkis a simple application of this geometric approach, asshown in Figure 3. The volatility of the benchmark(benchmark risk) is represented by the base of thetriangle, the volatility of the portfolio (portfolio risk)is represented by the side of the triangle drawn withthe solid line, and the portfolio's tracking error isrepresented by the side of the triangle drawn with adotted line. The correlation between the benchmarkand the portfolio is represented by the angle o; and

Figure 3. Portfolio and Benchmark Risk Analysisin Geometric Terms

using strictly numbers, I have portrayed it as part ofa triangle.'

One of the tools we use at Brinson Partners iswhat I refer to as the correlation protractor. JohnZerolis, one of the more quantitative-oriented peopleat Brinson Partners, generated the protractorby com­puting the correlation associated with each angle. Weuse the protractor for discussions in which immedi­ate visual representations are useful. One of the inter­esting things people notice when looking at thatcorrelation protractor is that not all correlationchanges are created equally in risk space. Suppose acorrelation goes from 0.9 to 1.0. This might not seemlike a big change, but moving from 0.9 to 1.0. is a 26°angle on the protractor. Similarly, a 26° angle fromzero moves the correlation from zero to about 0.45.In risk space, a movement in correlation from zero to0.45 is similar to a movement in correlation from 0.9to 1.0. This relationship is readily apparent from ageometric representation but not at all obvious froma set of formulas.

Now suppose I want to know the volatility of thepound from a mark perspective. All I need to do isdraw a line connecting the pound and the mark andmeasure the length of that line. The dotted line inFigure 1 indicates that the length is 9.1 (hence thevolatility is 9.1 percent). In addition, if I look at theangle between the dotted line and the solid dollar/mark line, I can tell that from a mark perspective, thedollar and the pound have a correlation of 0.38.

This technique facilitates the ability to under­stand a single covariance matrix from the perspectiveof every investor in the world, regardless of the inves­tor's base currency. For U'S. investors, we focus onthe dollar vertex of the triangle. For German inves­tors, we focus on the mark vertex, and so on. We canuse any number of different base currencies. Withjust three currencies, we can geometrically representthe correlation matrix on a piece of paper; with fourcurrencies, we would need a three-dimensional tet­rahedron. With five currencies, visualization mustoccur in triangular or tetrahedral subsegments, butthe intuition is still the same.

One benefit of this approach, in terms of consis­tency, is being able to see the implications of a cova­riance matrix from any base currency perspective.Suppose we think that the United Kingdom is goingto join the European Monetary Union (EMU) and thatthe pound's correlation with the euro (represented bythe mark) will probably increase to 0.95 as the United

IFor further discussion, see Brian D. Singer, Kevin Terhaar, andJohn Zerolis, "Maintaining Consistent Global Asset Views (with aLittle Help from Euclid)," Financial Analysts Journal (JanuaryIFebruary 1998):63--69.

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RiskManagement: Principles and Practices

the vertical dashed line indicates the portfolio's resid­ual risk.

Portfolio, Benchmark, and Residual Risks.In the context of a single-index model, the return ofthe portfolio is equal to a benchmark bet and theresidual return, which is uncorrelated with thebenchmark. Similarly, portfolio volatility comes fromtwo sources-one that is perfectly correlated with thebenchmark bet, or systematic risk, and one that isuncorrelated with the benclunark risk, or residualrisk. So, in Figure 3, the line for residual risk is at aright angle to the line for the benchmark risk becausea right angle is associated with a correlation of zero.Thus, Figure 3 shows two right triangles, and conse­quently, the Pythagorean theorem (the square of thelength of the hypotenuse is equal to the sum of thesquares of the other two sides) can be used to helpwith the risk analysis. This approach allows us to lookat the risks visually. We do not have to wonder whatwill happen if the residual risk of our portfolio goesup by 10 percent: The residual risk line will become10percent longer, the correlation of our portfolio withthe benchmark will go down because the angle willincrease, and the volatility of our portfolio willincrease (the portfolio line will lengthen). We do nothave to calculate anything to achieve that intuitiveunderstanding.

Residual Risk, Benchmark Relative Bets, andTracking Error. The right-hand, shaded triangle inFigure 3 shows residual risk, benchmark relativebets, and tracking error. Tracking error can bethought of in this context as value-added risk-therisk of the portfolio from the perspective of the bench­mark, or the risk of the difference between the port­folio returns and the benchmark returns. In essence,what this figure indicates is that tracking error is acombination of two things: (1)the benchmark relativebet (the base of the shaded triangle), which is theportion of active management that involves anincrease or decrease (as in this example) in bench­mark exposure, and (2) the residual risk, which is thatportion of the risk of active management that is notin any way correlated with the benchmark.

Ex Post Analysis. In a portfolio performancesense (an ex postsense), this geometric approach is atool that can help investors understand the overallperformance of their portfolios a little more intu­itively and clearly. Suppose I am a plan sponsor andone of my managers comes to me and says, "Thebenchmark has a volatility of x, the portfolio has avolatility of y, and the beta is Z." From that informa­tion, not only can I compute the correlation, deter­mine the cosine, and create the entire triangle,including the tracking error and residual risk (even

76

though the manager did not give me that informa­tion), but I can also quickly visualize and gauge thetracking error and residual risk without doing anycomputations. Although I could use algebraic or trig­onometric formulas to calculate the tracking error,using geometry is often easier because it allows meto visualize how the various risks move relative toeach other. As in Figure 3, I can see that the residualrisk of the portfolio is found by dropping a perpen­dicular line down from the point for the portfolio; Ican see that the base of the left-most triangle, foundby multiplying the beta times the benchmark risk, isthe systematic risk.

Ex Ante Analysis. From an ex antestrategy per­spective, the geometric view also helps in makingdecisions about changing the portfolio. For example,it can help investors understand how a certain strat­egy or change in strategy might affect a portfolio inabsolute and/or relative risk terms. Say we have aportfolio that holds some cash, and we think thattaking out that cash might reduce the tracking error.If we take out the cash, we do not change the portfo­lio's correlation with the benchmark. All we do isincrease the risk, so we have to make the line for theportfolio longer. Does increasing the portfolio linedecrease the tracking error? Not necessarily. Thetracking error decreases to a point but then begins toincrease again. Having a risk hedge in the portfoliomight reduce risk or it might increase risk relative tothe benchmark, which is easy to see from a geometric,visual perspective.

Portfolio ConstraintsPortfolio managers more often than not operateunder a variety of constraints, such as beta, trackingerror, or residual risk. But implementing those con­straints can cause difficulties. Once again, geometricinterpretation can be used to portray feasible sets ofalternative portfolios that are consistent with clientconstraints.

Beta Constraint. Suppose a client wants anessentially defensive portfolio. Figure 4 shows fourportfolios that have a beta of 0.9. I can create manyportfolios that have a beta of 0.9, and some of thoseportfolios might be considered defensive, but somewould not. Portfolio A, for example, would likely beconsidered defensive. It has a low volatility, and ithas relatively low tracking error and relatively lowresidual risk. When the correlation with the bench­mark is decreased while maintaining the beta of 0.9,the volatility of the portfolio has to increase. PortfolioD still has a beta of 0.9, but its volatility greatlyexceeds that of the benchmark, and it has a relatively

©Association for Investment Management and Research

Risk Analysis

Figure 4. Portfolios with Constant Beta of 0.9 would have a volatility of 10 percent and Portfolio Fwould have a volatility of 20 percent. Figure 5 clearlyillustrates that a tracking-error constraint still per­mits wide variations in volatility, beta, and residualrisk.

Portfolios

Residual Risk Constraint. I can also constructa number of portfolios that have the same residualrisk, as shown in Figure 6, but those portfolios aredecidedly different from each other. Portfolio A hasrelatively low volatility but relatively high trackingerror. By increasing the risk of the portfolio and itscorrelation with the benchmark, I get to Portfolio C.All three portfolios in Figure 6 have the same residualrisk, but Portfolio C has the highest volatility and thelowest tracking error. Thus, a constraint on residualrisk places few limits on volatility, beta, or trackingerror.

Figure 6. Portfolios with Constant Residual Risk

ResidualRisk

DTI

C 1II

B +I

A+II

I I0.1 (J' Benchmark

IJ"Bl'Ilchmark

0.9 (J' Ben,hmark

~

BenchmarkI-----------=----------il

substantial tracking error. All of the portfolios inFigure 4 have a beta of 0.9, but they are very differentportfolios; the beta constraint still allows dramati­cally different levels of portfolio risk, residual risk,and tracking error.

Figure 5. Portfolios with Constant Tracking ErrorLess than 5 Percent

Portfolios D

~" ~2\.. EB ..". : .:0. ' ..~.::.......•. F

BenchmarkI

is equal to its tracking error of 5 percent. Its volatilityis slightly greater than that of the benchmark, whichis very different from Portfolio A. Portfolio F still hasa tracking error of 5 percent and no residual risk,which sounds a lot like Portfolio A, but Portfolio F ismuch more volatile than Portfolio A. In fact, if thebenchmark has a volatility of 15 percent, Portfolio A

Benchmark C BI

(fBellchmQrk

(T Tracking Error

~A . B. ~T

'. '. ". :'1 I1'1-.,;-.. :' 1 I (J'ResidualRISk

..._=-L-__-'-::_.~... .J 1Benchmark

Multiple Constraints. Using this type of analy­sis allows one to look at the interactions of the invest­ment guidelines imposed on a manager. Figure 7shows a simple example of this type of interaction, inwhich the portfolio has two constraints. The firstconstraint is that the total risk cannot be any greaterthan that of the benchmark, indicated by the circlewith the center at Point A and the radius equal to the

Figure 7. Feasible Portfolios with Given TotalRisk and Tracking Error

5% I

0' lracking Error

(1Benchmark

Tracking-Error Constraint. Suppose a man­ager or a plan sponsor wants a portfolio with a track­ing error of 5 percent or less. Again, I can create anumber of portfolios that have a tracking error of 5percent, as shown in Figure 5. I simply draw a circlewith a radius length of 5, representing a trackingerror of 5 percent, around the benchmark position.Portfolio A, which can be formed by combining thebenchmark with cash, has a tracking error of 5 per­cent; it also has no residual risk and a relatively lowvolatility. Portfolio D has a beta of 1; its residual risk

©Association for Investment Management and Research 77

RiskManagement: Principles and Practices

benchmark (Point B).The portfolio can be anywherewithin that circle. The second constraint is that thetracking error cannot be greater than some specifiedamount, indicated by a semicircle around the bench­mark point (B) with a radius equal to the tracking­error constraint. When I combine those two con­straints, the only feasible portfolios are within thecross-hatched area. Consequently, the beta cannot begreater than 1, and the correlation cannot be anythingless than about 0.9. Portfolio P represents maximumtotal risk and maximum residual risk, and the mini­mum risk portfolio is Portfolio C.

A simple example provides a good illustration ofthe interaction of multiple constraints. Consider aportfolio with the same risk as the S&P 500 Index butwith a beta, with respect to the S&P 500, of 0.8. Onthe surface, those constraints sound fine, but lookingat the implications geometrically may indicate other­wise. First, we draw a line whose length representsthe volatility of the S&P 500. Because the portfolioand the benchmark have the same volatility, the betaand the correlation both are 0.8. Second, we draw aline whose angle corresponds to a correlation of 0.8

78

and that has the same length as the S&P 500. That linerepresents the portfolio. A straight line to connect theS&P 500 and the portfolio reveals that the trackingerror is 8-9 percent. Thus, the client's constraintsseem reasonable-same volatility as the benchmarkand a beta of O.8--but those constraints effectivelycreate a disguised risk: tracking error of 8-9 percent.Does the client really want a portfolio with a trackingerror of 8-9 percent? Probably not.

ConclusionGeometrically displaying the risk characteristics of aportfolio and its associated benchmark is a simple butpowerful tool. The geometric representation of port­folio performance and portfolio strategies helps insimultaneously analyzing multiple risks-absoluterisk, relative risk, systematic risk, residual risk, andtracking error. The geometric decomposition alsoproduces an intuitive understanding of the interac­tions, sometimes subtle and often unintended, thatresult from imposing portfolio constraints.

©Association for Investment Management and Research

Risk Analysis

Question and Answer SessionBrian D. Singer, CFA

Question: Can you representinformation ratios geometrically?

Singer: Yes, information ratioscould be represented by drawingwhat are known as iso-return linesin Figure 3. These lines might startat zero return (cash return if theanalysis is in risk-premium terms)at the dollar vertex of the triangleand go out in parallel fashion atreturn levels of 5 percent, 10percent, 15 percent, 20 percent,and so on. Having now superim­posed these iso-return lines overthe risk triangle, we can begin todo return and risk analysis simul­taneously.

Question: How do you incorpo­rate fundamental factors with thisapproach?

Singer: We use geometric riskanalysis, looking for examples ofthe risk relationships between aportfolio basket of securities andan industry or other factor basket.In the risk triangle, the benchmarkline could be thought of as theindustry or factor basket, with thelength of the line indicating thevolatility of that industry or factor.The angle at the dollar vertexrepresents the portfolio's correla­tion with respect to the industry orfactor and the loading on theindustry or factor measured just as

the benchmark bet (systematicrisk) would be measured. Thiswould be a univariate loading onone industry or factor, but we canalso do multivariate loadings withmultiple industries and factors.

In fact, that is how we buildour forward-looking covariancematrix-by considering country,currency, equity market, and bondmarket factors. We do not andcould not build thousands of pair­wise correlations in any consistentway. Rather, what we do is buildaggregate factors, which might beregions, industries, and so on, andthink about what the loading ofeach market is on those various fac­tors.

©Association for Investment Management and Research 79