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John M. Longo, Ph.D., CFA Rutgers Business School
The MDE Group
What We Know and Don’t Know About Risk
The Danish Forum for Performance Measurement Copenhagen, Denmark, June 12, 2014
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Outline
1) Motivation for Presentation
2) What We Know About Risk
3) What We Don’t Know About Risk
4) Methods for Navigating Risk in an
Uncertain World
2
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Motivation
Well known financial textbook, Brealey & Myers
What we know about Finance:
Net Present Value
The Capital Asset Pricing Model
Efficient Capital Markets
Value Additivity and Law of Conservation of Value
Capital Structure Theory
Option Theory
Agency Theory
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Motivation (2)
What we don’t know about Finance:
What determines project risk and present value?
Risk and return – what have we missed?
How important are the exceptions to Efficient Market
Theory?
Is management an off balance sheet liability?
How can we explain the success of new securities and
new markets?
What risks should a firm take?
What is the value of liquidity?
How can we explain merger waves?
Why are financial systems so prone to crisis?
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Mark Twain Quote
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We Know: Long-Term Risk-Return Relationship: Unfortunately it May Take 20 Years to Work !
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Detail on Long-Term: Decades with Zero Return
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We Know: Performance Rankings Are Erratic
Source: JP Morgan Guide to Markets
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We Know: Diversification Reduces Risk
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My ventures are not in one bottom
trusted, Nor to one place; nor is my
whole estate upon the fortune of this
present year: Therefore my
merchandise makes me not sad.
Antonio, in William Shakespeare's
"The Merchant of Venice", Act 1,
Scene 1.
Shakespeare on Risk Management (1597)
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We Know: Diversification Is A (Modest) Free Lunch
Source: JP Morgan Guide to the Markets, 2Q 2014.
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68% 66%
88%
Cash Outperforms
32%
Cash Outperforms
34%
Cash Outperforms
12%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Cash vs. Stocks Cash vs. Bonds Cash vs. Both Stocks and Bonds
Bonds Outperform
Stocks Outperform
Either Stocks or Bonds
Outperform
FREQUENCY (RATE) OF OUTPERFORMANCE FOR CASH Vs. STOCKS & INCOME
OVER 1-YEAR PERIODS (1926-2011)
We Know: Cash is Rarely King
Source: Fidelity Investments
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We Know: Interest Rates are Tied to Inflation
Source: J.P. Morgan Guide to Markets, 2Q 2014
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We Know: Interest Rates Impact Risk Through the Time Value of Money
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Buffett:
“Portfolio Theory was
invented by Aesop in 600
B.C. when he said, ‘A
bird in the hand is worth
two in the bush’.”
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We Know: The Taylor Rule and the Fed Funds Rate
Interest rates can’t fall below
zero, so the Fed or ECB must
use atypical monetary policy
in combinations with large
government stimulus.
Source: Paul Krussgman, “Zero lower bound
blogging,” New York Times, January 17, 2009.
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Although we cannot agree on the precise definition of risk, there is a more general consensus on the factors or levers that drive risk:
Market Exposure (e.g. Beta, Duration, etc.)
Leverage
Concentration
Liquidity
Quality
Transparency
Lesson: Watch the risk levers ex-ante
We Know: Most of the Drivers of Risk: Unfortunately, We Can’t Forecast Risk Well
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We Know: Reversion to the Mean Over the Long Term
VIX Example: Eventually reverts back to around 18-20 after shocks dissipate.
Many other examples (e.g. P/E, credit spreads, etc.)
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Bubbles don’t repeat exactly, but the boom / bust cycle continues. Fear and greed are inextricable parts of human nature.
Tulip Bubble
South Sea Bubble
“Nifty Fifty” of the 1970s
Merger Mania of the 1980s
Internet Bubble
Credit and Real Estate Bubble
Social Media Bubble (e.g. WhatsApp, Snapchat)
Cloud Computing Bubble
We Know: Bubbles Repeat Due to Human Nature
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We Know: Prices May Be Nonlinear (Bubbles Possible)
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We Know: Prices May Be Nonlinear (WhatsApp)
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Price tag:
$19
Billion!
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We Know: Prices May Be Nonlinear (Snapchat)
20
Snapchat
rejects $3
billion cash
offer from
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We Know: Security Prices Not Normally Distributed Dow Jones Example (Actual Distributions)
Source: PIMCO
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We Know: Black Swans Exist
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Black Swans cannot be predicted consistently, but their impact may be limited if we control the risk levers carefully and buy (cheap) insurance.
Examples of cheap insurance:
Deep out of the money options or other derivatives, before volatility spikes.
• Your portfolio will still take a hit after the black swan arrives, but losses may be more manageable.
Dealing With Black Swans
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We have known for many years that volatility tends to follow volatility (e.g. ARCH / GARCH models).
Q: Why? A: Investor psychology, delayed reaction to news, momentum trading, margin calls, and other reasons.
Hence, some volatility can be predicted (e.g. the second leg).
Risk Outside of Black Swans
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Predicting the 2nd Leg of Risk
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Cut your losses short and let your winners run.
Gain more on your winners and lose less on your losers (i.e. impact ratio).
Never fight the tape.
Bet bigger if more trades are going in your favor; otherwise, bet lesser amounts of capital.
Try to be greedy when others are fearful, be fearful when others are greedy. (Attributed to Warren Buffett)
We Know: Conventional Wall Street Wisdom On Risk
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There is no uniformly agreed upon definition of risk.
Most people view risk as the chance of losing money or
not achieving an important goal.
Others may view risk as volatility, or performance relative
to a benchmark.
Modern finance theory suggests that risk is to be voided,
unless you are compensated with extra return.
We also can’t effectively forecast the first leg of risk (e.g. Black Swan events).
We Don’t Know: How to Precisely Define Risk (Even Though We Know Most Of Its Levers)
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We Don’t Know: Equity Correlations Over Time
Source: J.P. Morgan
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We Don’t Know: Country vs. Industry Effects Ratio Of Country Effects To Sector Effects
Source: BARRA
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We Don’t Know: How Market Risk Changes
Using equities as an example, we know market risk is not simply driven by beta. Other factors are important, but not in any consistent manner:
Examples: Industry effects, interest rates, oil prices, political risk (e.g. Mideast, Europe), etc.
Suggests APT Model probably more applicable to the real world (e.g. BARRA type models).
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We Don’t Know: What Is Optimal Diversification?
The answer, according to various sources, ranges from 20 to 300 or more.
Famous “stock pickers” and early academic studies suggest something closer to the lower number.
They claim it is important to know what is in the basket rather than having so many eggs (i.e. stocks) that you cannot adequately follow.
Arguably, the stock market has become more volatile in recent years.
• Increases in volatility may be due to increases in hedge funds, program trading, higher debt loads, higher correlations due to globalization, and short-term investor mindset.
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Snapshot of Buffett / Berkshire Stock Portfolio
Source: WhaleWisdom.com
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Top 13F Holdings on 03/31/2014
Stock % of Portfolio
Wells Fargo & Company 21.7943%
The Coca-Cola Company 14.62%
American Express Company 12.9046%
INTERNATIONAL BUSINESS MACHINES
12.4396%
Wal-Mart Stores Inc. 4.1948%
Berkshire’s Top
10 holdings
comprise 82% of
its portfolio.
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We Don’t Know: The Distribution of Security Prices Fat Tailed Distribution 1: Levy Distribution
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We Don’t Know: The Distribution of Security Prices Fat Tailed Distribution 2: Cauchy Distribution
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We Don’t Know: Why Decoupling Doesn’t Hold
Emerging
markets are not
decoupled from
developed
markets despite
growing GDP.
They are part of
the “Risk On”
trade.
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Because of These Unknown Risks We Often Use Band-Aids (i.e. Heuristics)
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How to Deal with Risk
Watch risk levers, buy cheap insurance (e.g. deep out of the
money put options or other derivatives).
Use investment policy constraints to prevent big bets
Follow a macroeconomic approach
Utilize dashboards
Utilize bubble risk charts
Conduct stress tests
Examine linkages among risks (Davos Economic Forum)
Combine fundamentals with technicals and behavioral
finance
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Global Macro Approach: Effective In Dealing With Risk?
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Sample Macro Indicator: ISM PMI Index
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Macro Indicator: China Bank Lending / Electricity Consumption
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Investment Mosaic or Dashboard
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Risk Factor Dashboard - Global Model Mix
Subprime Spillover
Recession
Terrorist Attack
Supply Chain Disruption
Natural Disaster
Surge in Int Rates
Depreciating DollarPolitical Turmoil
Real Estate Collapse
Market Crash
Health Epidemic
Tax Increase
Hedge Fund Failure
(Inv)Bank Failure
Private Equity Problems
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0% 45.0% 50.0% 55.0%
Probability of Event in %
Mag
nitu
de o
f Los
s in
%
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Stress testing empirically tests how the fund would have performed during historical or hypothetical high risk scenarios
Examples: Crash of 1987, Bear Markets of 2000-2002, 2007-2009,etc.
Stress testing is not very effective when dealing with “Black Swan” type events.
Stress Testing Funds
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VaR has a big practical problem
It doesn’t tell you how bad things will get in the left part of the distribution (e.g. bottom 5%) .
Need to examine Conditional VaR, also known as Expected Shortfall to attempt to more fully quantify left tail risk
Conditional VaR or Expected Shortfall Calculation
Take the average of the worst expected outcomes (e.g. bottom 5% of left tail).
Conditional VaR: Model Left Tail Risk
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Showing Linkages Among Risks
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Evolution of Risks: Likelihood
Source: World Economic Forum
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Evolution of Risks: Impact
Source: World Economic Forum
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Ben Graham Analogy: Market As A Pendulum
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Fear, March 2009 Greed, Internet Bubble
Long Run = Fair Value
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Technical analysis was once had the same level of respect as astrology. However, technical analysis does add some value due to the following:
(Illegal) Insider Trading
Legal Insider Trading (Director Trades, Bill Ackman 10% purchase of Allergan before takeover announcement)
News does not come out of a vacuum (Sometimes analysts do research, take a position, and give the information to reporters).
Investor psychology (chasing performance)
Self fulfilling prophecy(“placebo effect”)
Why Technical Analysis ≠ Astrology
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Coca Cola: Bear Market Overrides Fundamentals
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Bank of America Example: News Revealed Later
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Bank of America stock down 30%+ from Nov 11th – Dec 31st. Stock up
45% from Jan 1st to Feb 14th. What drove this strange performance? On
Feb 14th it was revealed John Paulson sold all of his shares in Bank of
America during the 4th quarter. (Initial stake was $2.2 billion)
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Behavioral Finance: Back to the Future
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John Maynard
Keynes:
"The markets are
moved by animal
spirits, and not by
reason."
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Behavioral Finance: Back to the Future
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Benjamin Graham:
"In the short-run, the market is a voting
machine."
(It is a popularity contest, influenced by
psychology)
"In the long-run, the market is a
weighing machine."
(It weighs or values earnings)
"The investor's chief problem – and
even his worst enemy - is likely to be
himself."
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Two people can look at the same exact picture (company or market) and come to different conclusions.
One says “Buy,” the other says “Sell.”
There is a human element in pricing (even adjusting for different time horizons and information sets).
One Lesson From The Picture
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Cycle of Market Emotions Impacts Performance
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Investor Performance Is Impacted by Behavioral Biases
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Investor Performance Consistently Subpar
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Positive Neutral Negative
Credit Conditions
Corporate Earnings
Monetary Policy
Energy Prices
Inflation
Valuations
Economic Activity
Geopolitical
Fiscal Policy
Dealing With Conflicting Signals Balanced Scorecard
Source: Fidelity Investments
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Questions?
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Biographical Sketch: John M. Longo, PhD, CFA
Dr. Longo is a Clinical Professor of Finance & Economics at Rutgers Business School, and Chief
Investment Officer (CIO) and Chairman of the Investment Committee for The MDE Group
(www.mdegroup.com), a registered investment advisor with $1.5 billion under management. The MDE
Group has been ranked as the 4th best independent investment advisor in the USA by Barron’s in
2007 and 2008. He is also CIO of MDE’s sister company, Acertus Capital Management.
Dr. Longo has appeared on CNBC, Bloomberg TV, Bloomberg Radio, Fox Business, BBC World,
wsj.com (video),The (Ron) Insana Quotient, Greatinvestors.tv and several other programs. He has
been quoted in the The Wall Street Journal, Thomson Reuters,Dow Jones MarketWatch, The Chicago
Tribune, The Star Ledger, Hedge Fund Alert, FundFire, and dozens of other periodicals.
He is author / editor of Hedge Fund Alpha: A Framework for Generating and Understanding
Investment Performance. He is a member of the Editorial Boards of The Journal of Performance
Measurement and The Journal of Financial Planning & Forecasting. He has served as consultant to
many financial service firms on a global basis and twice led Rutgers students to a personal visit with
Warren Buffett. Previously, he was a Vice President at Merrill Lynch & Co., Inc.
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Legal Disclaimers: Information contained in this document does not constitute personalized investment advice.
Information contained in this document does not constitute an offer to sell or solicitation to buy securities.
Any offer to sell The Alternative Fund, LLC or any other non-registered security will be made only to qualified investors pursuant to a
confidential offering memorandum.
All information contained in this presentation has been gathered from sources which The MDE Group, Inc. deems to be accurate.
However, inadvertent errors may occur.
Investing involves risks which may lead to losses. Different types of investments involve varying degrees of risk and there can be no
assurance that any specific investment will be profitable. The MDE Group, Inc. does not make any representation that any of its
investments on behalf of clients, including but not limited to any investments in The Alternative Fund, LLC or the Planned Return
Strategy, Accelerated Return Strategy, or the Third Rail Strategy or any other investment strategy, will or is likely to achieve returns
similar to those shown in the performance results in this presentation.
Past performance is not a predictor of future results. It should not be assumed that any information discussed herein will prove to be
profitable or that decisions in the future will be profitable or provide similar results.
Calculation methodologies are available from The MDE Group, Inc. upon request.
Any discussion of tax matters contained within this communication should not be used for the purpose of avoiding U.S. tax related
penalties or promoting, marketing, or recommending to another party any transaction or matter addressed herein.
The MDE Group, Inc. disclaims liability for any expense incurred or any damage or loss sustained which may be attributable, directly or
indirectly to the use of or reliance upon any information provided.
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