iac 2q2012 issue

8/13/2019 Iac 2Q2012 Issue

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Letter from David Remstein

Welcome to the latest issue of J.P. Morgan’s Investment Analytics & Consulting newsletter,which aims to provide informative and thought-provoking articles on topics relating toportfolio optimization. In this issue we provide an in-depth analysis of Stress Testing anddiscuss its implementation as an effective risk management tool within an investmentmanagement organization. Security Level Contribution to Return Analysis is covered in our‘Product Highlight’. We welcome your thoughts and suggestions, and hope that this issueprovides you with useful information.

David RemsteinManaging Director and Global Executive, Investment Analytics & ConsultingJ.P. Morgan Worldwide Securities [email protected]

Second Quarter 2012 Edition

About J.P. Morgan’s Investment Analytics & Consulting Group

J.P. Morgan’s suite of Investment Analytics and Consulting services provides clients with the

information they need to make more informed investment decisions through innovative and

forward-looking solutions. J.P. Morgan provides Investment Analytics & Consulting services to

over 300 clients globally with over 9,000 institutional portfolios, representing approximately

$2 trillion in assets. Our diverse client list includes corporate and public DB/DC pensions, investment

managers, endowments and foundations, corporate treasuries, insurance companies, central banks and

hedge funds.

Having the broadest and deepest Investment Analytics and Consulting product offering in the market,

J.P. Morgan offers security-level, multi-currency performance measurement (monthly and daily) using

J.P. Morgan or third party accounting; characteristics and attribution at the asset class, sector, country,

and individual security level; ex-ante risk measurement (including Risk Budgeting and security-level VaR);

investment manager analysis, universe comparison, and peer grouping; global consolidated reporting

for multi-national plans; and consultative services in the areas of liability and plan allocation strategy.

For further information, please visit www.iac-opal.com or www.jpmorgan.com/visit/iac,

or contact:

Americas & Asia:

Mark Huamani

Managing Director

[email protected]

Europe, Middle East, Africa:

Alex Stimpson

Executive Director

[email protected]

Australia:Stuart Hoy

Vice President

[email protected]

Any opinions, estimates and forecasts offered in this newsletter constitute the authors’ judgment as of the date of the materials and are subject to change without notice, as are statements of financial market trends, which are based

on current market conditions. We believe the information contained in this newsletter to be reliable but do not warrant its accuracy or completeness. This material is not intended as an offer or solicitation for the purchase or sale

of any financial instrument. The views and strategies described may not be suitable for all investors. This material has been prepared for informational purposes only and it is not intended to provide and should not be relied on for

investment, accounting, legal or tax advice. Any opinions, estimates and forecasts are solely those of the authors and not of J.P. Morgan.

This document contains information that is the property of JPMorgan Chase & Co. It may not be copied, published, or used in whole or in part for any purposes other than expressly authorized by JPMorgan Chase & Co.

Copyright © 2012 JPMorgan Chase & Co. All rights reserved

Table of Contents

Stress Tests:

Aspects and Considerations 2

Product Update:

Security Level Contribution

to Return Analysis 4

Global Markets 7

8/13/2019 Iac 2Q2012 Issue

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Hypothetical Stress Testing

Stress Tests: Aspects and Considerations

By Andrew Robertson, [email protected]

Stress testing has become an integral part of portfolio risk management

to help eliminate potentially large losses from extreme events. This

article explores the aspects and considerations needed to implement

hypothetical stress testing as an effective risk management tool within

an investment management organization.

Portfolio Risk Management

Perhaps the most important element of any risk management framework

is buy-in from the top. Senior management within an organization needs

to promote a ‘risk culture’ where the identification and measurement of

risk becomes a central business driver. For senior management the risks

need to be identified, measured and managed.

Statistical models, such as Value at Risk, have long been used for risk

management purposes. In general, VaR models assume normal market

conditions. Under extreme market conditions, the underlying assumptions

of these models break down. In these situations, stress testing has been

used as a complementary technique to identify potential loss.

Stress tests fall into three main categories: scenario analysis, historical

stress testing and hypothetical stress testing. Scenario analysis identifies

a portfolio’s sensitivity to an individual risk factor, for example, a 100

basis point shock to interest rates. Historical stress testing recreates a

past extreme event, such as the September 11 attacks. Hypothetical stress

testing uses potential future extreme events to stress a portfolio. Examples

include the break up of the Eurozone or a severe downturn in China.

The obvious difference between hypothetical stress tests and the twoother forms is the requirement to create a complex severe event not yet

encountered. This presents unique challenges and can take considerable

resources to produce. However, hypothetical stress tests may allow an

organization to prepare for events in advance and lower the chances of

a shock and awe response if the event were to occur.

Hypothetical Model Building Blocks

Hypothetical stress test models are comprised of four key building

blocks1 - an extreme hypothetical scenario to define a set of exogenous

risk drivers, a data generating process to map the exogenous factor

to a set of exposure specific risk factors, an exposure, and finally, a ris

measure. These building blocks are illustrated below.

Stress tests perform two main tasks: act as an instrument of measuremen

for limit setting and capital allocation or to act as a tool for communication

allowing the discussion of risk within an organization to take place. If the

purpose of the exercise is for communication, the priorities for the stres

test model design are transparency and story telling suitability.1 The mode

design should be simplistic, with few systematic risk factors and simple

relationships between variables.

If a stress test is to be used as a measurement instrument, the priority is mode

accuracy and forecast performance.1 In this case, a complex model should

be created, containing many intricate parts and risk factors. Mechanisms

such as feedback loops should be incorporated, liabilities considered and

sophisticated quantitative models for co-movement employed.

The type of portfolio also plays a fundamental role in the design of the stres

test model. This requires an understanding of the way the fund manage

makes money and to what risk types they are exposed. For example, the

model design for a credit risk incorporating probabilities of default will b

fundamentally different from a market risk stress test model.

Scenario Development

The purpose of a stress test is to explore the behavior of a portfolio unde

extreme conditions and make decisions based on their results. Developing

a hypothetical stress scenario is a complex process because it require

not only envisioning an event that hasn’t happened before, but it also

needs to be able to persuade others the event is plausible. If a scenario

is too extreme, it may be hard to justify to decision makers and could be

dismissed as too unlikely to occur. If a scenario isn’t extreme enough, it wil

provide limited information and may be disregarded as too insignifican

to act on. Therefore it is important to find the right balance between

severity and plausibility when developing a scenario. This is best achieved

through the collaboration of different experts within an organization

such as risk managers, economists and fund managers. Using thei

expertise and experience, a state of the world can be formulated based

Exhibit 1: VaR capturing risk as a plane, stress testing capturing riskas a point.

Source: Yuko Kawai, Bank of Japan, 2006

HypotheticalScenario

(Euro breakup)

DataGeneratingProcess ofSystematic

Risk Factors(Regression

Model)

Exposure

(Portfolio)

Risk Measure

(P&L)

Exhibit 2: Stress test building blocks.

Source: Drehmann 2008

Risk Manager

EconomistFund

Manager

SeniorManagement

Exhibit 3: Iterative cycle of hypothetical scenario generation

Source: J.P. Morgan

8/13/2019 Iac 2Q2012 Issue


Hypothetical Stress Testing

on possible future events and then cross checked by senior management.

Using this approach a scenario may not only be more realistic, but will also

incorporate the culture and risk appetite of the organization.

Stress testing is most effective when a number of hypothetical stresses are

applied to give an overall risk profile of a portfolio. The ultimate goal is to

create a library of scenarios covering many possible future events, so scenario

generation should be iterative and ongoing. To keep scenarios relevant, they

should be periodically screened, challenged and cross checked in light of

changing economic events and the risk profile of the portfolio. The process

should be dynamic and engage people from across the organization.

The most obvious starting point to develop a stress scenario is envisioning

a future extreme world event. As well as having a degree of imagination,

this calls on using economic fundamentals to create a forecast model. The

extreme event is played through the model, with considerations made for

arbitrage relationships between asset types and relationships between

currencies. The laws of supply and demand are explored and challenged

to produce a set of stress systematic risk factors such as global indices and

major currency pairs.

Another popular approach to building an extreme event is to consider the

interrelationship of financial markets and the effect a liquidity shock mayhave on it. The technique starts with a ‘thought experiment’ on liquidity

key drivers. Features to be considered are the interconnection of the

financial system through advances in information technology and how this

can amplify events through feedback in the financial system. The effects

of market participants all managing risk in the same manner is another

element that may need to be explored. An example of this technique might

be an event causing a sharp increase in market risk and dealers exiting

positions to avoid breaching trading limits. This contributes to further

volatility and triggers action to be taken by other market participants

resulting in herd behavior and further feedback in the system. The behavior

spreads to other markets through the deterioration in liquidity and the

inability to implement hedging strategies, thus causing further increases in

volatility. As a result, a major market event unfolds.

A third technique is to identify a maximum portfolio loss using mathematical

optimization to create a hypothetical event scenario. The worst case

scenario can be created by modifying the systematic risk factors within a

stress test model under plausibility constraints, while ensuring the events

are sensible due to the mathematical nature of the technique.

Interpretation of results

Hypothetical stress testing does not act as a crystal ball for future events.

Stress testing is a risk management tool that requires both a quantitative

and qualitative approach to establish the risk profile of a portfolio.

The qualitative element of stress testing has led to skepticism in the pastand the rationale results are of little use without associating a probability to

an event. Yet, this is the nature and challenge inherent in risk management.

Trying to assign a probability to a hypothetical stress test in isolation seems

to be a dangerous exercise, which could lead to a false sense of security

in numbers.

One answer is not to look at single stress tests, but to apply a number of

scenarios to a portfolio and use judgment to rank each on a probability o

occurrence vs. impact of risk chart.

The result is both intuitive and informative, giving a quick, clear view o

which scenarios warrant most attention, as well as an overall risk profile othe entity being stressed.

Further insight can be gained by building up a history of probability/impac

charts over time, thus allowing the ability to perform trend analysis on

changes to business and the economic environment.

The process of interpreting the results of stress tests also aid psychologica

preparation to events. Bringing different members of an organization

together to discuss the topic of risk helps raise decision and though

awareness within an organization. In turn, this helps formulate contingency

plans and impact mitigation, lowering the chances of a shock and awe

response to market events.

Conclusion

The business of risk management is a balancing act of risk against return

It sometimes feels like the playing field is not even, as small frequent

opportunities to make profit are offset by large infrequent losses. The aim

of hypothetical stress testing is to explore weaknesses in a portfolio unde

extreme circumstances to help mitigate these losses. But it is clear tha

there is no one-size-fits-all formula for stress testing in an organization

This is determined by the culture, the objective at hand and the overall risk

appetite.

A hypothetical stress testing program needs to have buy-in from all aspect

of the organization. In some sense, stress testing is born of a state of mind

where ideas can be explored and where people and methodologies are open

to be challenged. It is most important that senior management is involved

in the design process, as ultimately they will be the ones making decision

on the back of any stress scenario. As with any practice, experience gains

understanding and grows confidence in a method.

Exhibit 4: Probability impact chart

Source: J.P. Morgan, www.mindtools.com

References:

BIS 2009, ‘Principles for sound stress testing practices and supervision’

PRM Handbook Volume III, pages 173 – 184

Kawai 2006, ‘Stress Testing at Major Financial Institutions: Survey Results and Practice’

1 Drehmann 2008, ‘Stress Tests: Objectives, Challenges and Modelling Choices’ Riksbank Economic Review.

8/13/2019 Iac 2Q2012 Issue


Product Update

Security Level Contribution to Return Analysis

By James Eaton, [email protected]

While traditional attribution analysis models allow clients to understand how and why their investment manager achieved any over or under

performance, it relies on a suitable benchmark being in place that can be deconstructed to the level required for the analysis (e.g., economic sectors,

countries, securities, etc.). While in many cases a suitable benchmark does exist and attribution can be provided, there are increasingly many types

of alternative investment strategies for which a suitable “attribution” benchmark is not available (or required). In these cases a more appropriate and

relevant tool for the client is to understand the drivers of the absolute return of a portfolio through the use of contribution to return reporting.

J.P. Morgan’s Investment Analytics and Consulting group (IAC) has developed a range of contribution to return reports which enable clients to

understand the drivers of return, whether it be decomposing a Total Pension Scheme return into underlying asset class/investment manager

contributions, or as we shall cover in this article, a security level contribution to return analysis.

Available via the J.P. Morgan ACCESS®, Views Portfolio Reporting tool, IAC can provide clients access to daily or monthly security level contribution to return

reporting which allows clients to decompose their Portfolio or Composite returns into the underlying security level contributors. The reporting is available

for any type of portfolio, covering any asset class and security, whether long or short. It is therefore a particularly valuable tool when looking to explain

the impact of derivatives, exchange traded or OTC’s, hedging or short positions within a portfolio. Alternatively, IAC clients can use this reporting function to

compare portfolios with the same mandates in order to understand how one investment manager’s selection decisions compare to another’s.

Methodology

Contribution to return methodology has traditionally used a weight (%) multiplied by return approach to generate the contribution to return. Whil

this methodology will produce an accurate representation of an asset’s contribution, it does rely on accurate returns being generated across ALL

security positions to ensure contributions are accurate and roll up exactly to the portfolio return. For certain situations that can prove to be more

difficult, such as where OTC’s are held, market values moving from positive to negative or if there is heavy restructuring activity within a portfolio.

To get around this while still calculating an accurate contribution, IAC uses a monetary gain/loss approach to calculate the security contribution to

return. Monetary gain/loss is defined as:

Ending market value - Beginning market value - Net cash flow*

Even in this challenging situation, every security position fed from the accounting system during the holding period, whether they are OTC derivatives

cash receivables/payables or expense accruals, will have at least one of these three data points available in order for the monetary gain/loss to be

calculated. Considering the value of a portfolio is always the sum of the underlying security values, it is therefore consistent that the sum of the security

level monetary gain/loss will always roll up to the total portfolio level monetary gain/loss. Conceptually, it is this relationship that ensures that when we

come to calculate the security level contributions they will always sum up to the total portfolio level return.

So how do we move from a monetary gain loss value to a contribution to return? We do this by firstly working out the weight that each security’s

monetary gain/ loss forms of the total monetary gain/loss. We then multiply this weight by the total return of the portfolio, whether Net or Gross o

fees, to produce the security’s contribution to return.

Security contribution to return = Security monetary gain/loss x Total portfolio return

Portfolio monetary gain/loss

This formula not only provides an accurate calculation of contribution, which takes into account any cash flow timing method set up on the portfolio, but

also ensures contributions roll up to the total portfolio even where individual security returns may be missing or difficult to produce.

Multi-period contribution methodology

The methodology outlined above is only accurate for any given single period (one day or one month if reporting frequency is monthly). For longe

periods, to ensure the most accurate calculation of the contribution is reported, the security contributions for all single periods within the total

period are calculated and then aggregated using an appropriate smoothing algorithm. For example, a three month contribution to return report for

daily service client would calculate daily contributions for each day within the three month period and then aggregate. This extensive but automated

calculation ensures highly accurate results over longer periods.

Outputs

As the calculation is always at a security level, the contribution being additive allows us to roll up the contributions to any level within a portfolio’s

asset class hierarchy. To utilize this, IAC contribution reporting allows clients to group securities by a number of different aggregation options

depending on the classification scheme required. The following graphics show examples of available grouping options. Alternatively, clients may just

wish to see a full security list sorted by best to worst contributors or a Top 10/Bottom 10 output.

*Net value of all transactions; purchase, sales, dividends, interest etc

8/13/2019 Iac 2Q2012 Issue


Product Update

Security contribution to return by Economic sectors/industries

*Client can input “X” (e.g., 10)

Security contribution to return – Top X Bottom X*

8/13/2019 Iac 2Q2012 Issue


Composite level outputs

In addition to a portfolio view of the security contributors, the contribution to return reporting can also be performed at a composite level. When ru

at a composite level, an additional option is available which allows securities to be reported on an aggregated or un-aggregated basis. When run using

the aggregated option, security positions are aggregated across all underlying portfolios. Only one position per security is reported at the composit

level and no reference to the underlying manager holding that position is made. This option provides the same view of a composite as you see for

an individual portfolio. When the un-aggregated option is selected, the contribution report reflects each individual position per underlying portfolio

therefore you may see the same security several times if held by more than one underlying portfolio. Details of which portfolio is holding each positio

is shown on the report in this case. This option allows clients to see how each portfolio’s security position contributed to the overall composite return

The following graphics are examples of un-aggregated output.

Should you be interested in receiving contribution reporting as part of your performance measurement service from J.P. Morgan’s Investment Analytic

and Consulting group, please contact your IAC representative.

Security contribution to return – Composite Level – Un-aggregated view

This article is for informational purposes only. It is not intended as an offer or solicitation for the purchase or sale of any financial instrument or as an officialconfirmation of any transaction. All market prices, data and investment holdings within are solely for illustrative purposes. This document contains informationthat is the property of J.P. Morgan. It may not be copied, published, or used in whole or in part for any purposes other than expressly authorized by J.P. Morgan.

Product Update

8/13/2019 Iac 2Q2012 Issue


Global Markets

Multiple Asset Class Comparison as of March, 2012

By Karl C. Mergenthaler, CFA, William Pometto and Jessica Lin

[email protected], [email protected] and [email protected]

Index Monthly Return Trailing 3 months Year To Date 1 year 2 year 3 year 5 year 10 year

Russell 3000 (Gross) 3.08 12.87 7.18 12.18 24.26 2.18 4.67

MSCI EAFE (Net) (0.46) 10.86 (5.77) 2.00 17.13 (3.51) 5.70

MSCI Emerging Markets (Net) (3.33) 14.08 (8.80) 3.94 25.07 4.67 14.13

Barclays U.S. Aggregate Bond Index (0.10) 0.30 7.71 6.41 6.83 6.25 5.80

Merrill High Yield Index (0.10) 5.05 5.71 9.84 23.59 7.74 8.83

JPMorgan GBI Emerging Markets Bond Index (1.24) 10.42 1.08 5.77 13.88 3.83 8.97

NAREIT Index 4.84 10.49 11.29 17.96 42.21 (0.12) 10.43

Goldman Sachs Commodity Index (Gross) (2.35) 5.88

12.87

10.86

14.08

0.30

5.05

10.42

10.49

5.88 (6.21) 7.29 13.15 (2.86) 4.74

-15

-10

-5

0

5

10

15

20

25

Monthly Return Trailing 3 months Year To Date 1 year 2 year 3 year 5 year 10 year

Russell 3000 (Gross) MSCI EAFE (Net) MSCI Emerging Markets (Net) Barclays U.S. Aggregate Bond Index

Merrill High Yield Index JPMorgan GBI Emerging Markets Bond Index NAREIT Index Goldman Sachs Commodi ty Index (Gross)

(%)

U.S. Equity

• U.S. equities began the year with a solid performance. The Russell

3000 index generated a 12.87% return in the first quarter.

• The Russell 3000 was up 7.18% for the past year, and 4.67% over

the most recent 10 year period.

International Equity

• The MSCI EAFE Index experienced a 5.77% decline since the first

quarter of 2011 attributable to the ongoing stress posed by the

European sovereign debt crisis, but posted a 10.86% return in the

first quarter.

• The MSCI Emerging Market Index experienced a decline of 8.80%

for the past year, while continuing to produce impressive 3, 5, and

10 year returns through March 2012.

Fixed Income

• The Barclays U.S. Aggregate index produced an overall return o

7.71% for the past year.

• The Merrill High Yield index generated a return of 5.05% yea

to date.

• The J.P. Morgan GBI Emerging Market Bond Index posted a 1.08%

return for 1 year while 3, 5, and 10 year returns remain positive.

Real Estate and Other

• The NAREIT index over 12 months returned 11.29%, outperforming

the broader U.S. equity market and overcoming the macroeconomic

turmoil.

• The Goldman Sachs Commodities Index was up 5.88% for the firs

quarter but was still down 6.21% for the past year.

8/13/2019 Iac 2Q2012 Issue


Global Markets

Global Equities (ex-North America) as of March, 2012

By Andrew Farmer and Simon [email protected] and [email protected]

European Indices (all quotes in €)

0

20

40

60

80

100

120

140

160

180

0

2,000

4,000

6,000

8,000

10,000

12,000

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

U.K., France, Germany, Switzerland

FTSE 100 CAC 40 DAX 30 SMI 20 MSCI Europe (right axis)

Commentary:

European markets continue to be dominated by concerns on the continuing Sovereign Debt Crisis. The EMU has been the worst performing globa

region on a year-to-date basis. Spain came under significant stress again with the IBEX down 14% in EUR terms for the first quarter of 2012. It was thworst performing market in Europe and the gap with core European Markets (the Dax in particular) has widened further.

Commentary:

• The ASX200 index had a strong start to 2012 at AUD +6.9% (EUR +5.12%)

its best first quarter since 2006 and strongest quarter since the third

quarter of 2009; but even the currency gain in AUD to USD at +1.3% did

not keep it up with the strong performing world equity markets. The ASX

was driven by the strong underlying Industrial and IT sectors.

• Chinese markets experienced high volatility during the first quarter

of 2012. While the government has been acting to promote growth

(monetary policy shifting from containing inflation to promoting

economic growth), the markets have reacted negatively in March to

renewed fears of an economic hard landing. Overall, the market rose

+7.15% in euro currency terms.

• The Hong Kong Chief Executive election held late March along with

weak tourism inflows and resultant low retail sales in the first quarte

of 2012 halted the rise of the Hang Seng in March (HK$ -5.2%) which

had followed two strong months of growth in the year of the dragon.

• After two strong months driven by underlying property performance, the

FTSE Straits Times index began to stabilize late in the first quarter with

a move from Financials and Industrials to Consumer Discretionary as the

sector leaders.

• Japan was a stand-out of the bourse indices with Nikkei 225 gaining

+19.3% in local currency terms. The weaker yen boosted corporate

earning prospects.

• The Kospi rose around 12% during the first quarter, buoyed by

heavy net purchases by foreign investors. Cyclical sectors such as

shipbuilders, energy & chemicals and steels led the market growth

Expectations of improvements in the European debt situation added

to the positive growth.

0

1,000

2,000

3,000

4,000

5,000

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

ASX 2 00 Hang Seng Index Strai ts T imes Index

Australia, Hong Kong, Singapore

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Nikkei 225

Japan

0.0

0.5

1.0

1.5

2.0

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Kospi Index

South Korea

Asian Indices (all quotes in €)

Source: J.P. Morgan’s Investment Analytics & Consulting group, J.P. Morgan Equity Research, Morgan Markets, Bloomberg and Rimes

iac 2q2012 issue

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