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PORTFOLIO LESSONS FROM THE CRISISROBERT ENGLE
VOLATILITY INSTITUTE, NYU STERN
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STERN VIEW OF DODD-FRANK
Released November 2010
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LESSONS
• Many investors, CEOs, risk managers, ratings agencies, traders and regulators took more risk than they expected.
• Many of these same individuals were paid well to ignore the risks.
• Regulatory reform is designed to reduce the incentives to ignore risk. What about improving risk assessment?
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WERE WE PREPARED?WERE WE PREPARED?
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SHOULD WE HAVE KNOWN?
• Would a good econometrician and risk assessor have known that the financial crisis was coming?
• Would the crisis have been in the confidence set?
• Was there information that risk assessment typically misses?
• Would economics have helped?
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IS THIS AN EXAMPLE OF Sir David Hendry’s STRUCTURAL BREAKS AND PREDICTIVE FAILURE or Nassim Taleb’s BLACK SWAN?
• Quite possibly, but which models are we thinking about?
• Models which assume constant volatilities or correlations did very badly.
• VaR based on standard volatility models didn’t do so badly in this crisis.
• But were they good enough?
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3 Sigma Bands before Aug 2007
-.100
-.075
-.050
-.025
.000
.025
.050
.075
.100
90 92 94 96 98 00 02 04 06
DJRET -3*DJSD 3*DJSD
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Out-of-Sample 3 Sigma Bands after Aug 2007
-.15
-.10
-.05
.00
.05
.10
.15
08M01 08M07 09M01 09M07 10M01 10M07
DJRET -3*DJSD 3*DJSD
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Crisis Out-of-sample Standardized Returns
0
20
40
60
80
100
120
140
-3.75 -2.50 -1.25 0.00 1.25 2.50
Series: DJRET/DJSDSample 7/31/2007 7/16/2010Observations 773
Mean -0.021212Median 0.013111Maximum 3.261659Minimum -3.671674Std. Dev. 1.046813Skewness -0.367987Kurtosis 3.543005
Jarque-Bera 26.94260Probability 0.000001
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FORECASTING VOLATILITY in VLAB
• VLAB.STERN.NYU.EDU• VLAB forecasts volatilities of several
hundred assets every day with a variety of models
• Assets include equity indices, individual equities, bonds, FX, international equities, commodities, and even volatilities themselves.
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S&P500 and VIX: Sept 9,2011
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LAST THREE MONTHS
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US SECTORS
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INTERNATIONAL EQUITIES
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FORECAST PERFORMANCE IN VLAB
• During the financial crisis, the short run forecasts were just as accurate as during the low volatility period.
• One month ahead forecasts were less accurate during the crisis but were still within the 1% confidence interval of historical and theoretical experience.
• See Brownlees, Engle, Kelly,”A Practical Guide to Forecasting in Calm and Storm”
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SHORT RUN VS. LONG RUN RISK
• Widely used risk measures are Value at Risk and Expected Shortfall.
• These measure risk at a one day horizon (or 10 day which is calculated from 1 day)
• However, many positions are held much longer than this and many securities have long horizons. The risk for these securities is a long run measure of VaR or ES.
• There is a risk that the risk will change!!
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INVESTING IN A LOW RISK ENVIRONMENT
• Many investors took low borrowing rates and low volatilities as opportunities to increase leverage without much risk.
• Structured products such as CDOs were very low risk unless volatility or correlations rose.
• Insurance purchased on these positions made the risks even lower as long as the insurer had adequate capital.
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WHAT HAPPENED?
• Volatilities and correlations rose and all these low risk positions became high risk and impossible to sell without deep discounts.
• Insurance became worthless as insurers were undercapitalized. They did not foresee the risks.
• Options market and many forecasters including myself believed volatility would rise.
• Risk measurement does not have a good way to incorporate this information.
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HOW TO MEASURE TERM STRUCTURE OF RISK?
• Calculate VaR and ES for long horizons with realistic returns
• Use economic information to improve these estimates
• Continue to use Scenario and Stress Testing
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SIMULATED 1% QUANTILES FROM TARCH
• Using S&P500 data through 2007, estimate a model.
• Simulate from the model 10,000 times and calculate the 1% quantile.
• Assume either normal shocks or bootstrap from historical shocks.
2 21 0tt t t r th r r I h
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600
800
1,000
1,200
1,400
1,600
07M07 08M01 08M07 09M01
SPCLOSEQ_TARCH_BOOT_AUG07Q_TARCH_NORM_AUG07
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USING OPTIONS FOR LONG TERM RISK
• Ongoing research with Artem Voronov and Emil Siriwardane.
• Constrain simulation to have expected volatility that matches term structure of option implied vols.
• Realizations follow TGARCH.
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ONE YEAR S&P VaR SEPT 9,2011
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DAX 365 DAY VaR
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HOW FAST DOES VOLATILITY CHANGE? THE VOV
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LONG TERM RISKS
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WHAT CAN WE EXPECT?
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OR
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HEDGING A FINANCIAL CRISIS
• In a financial crisis, volatility rises and so do secure assets such as gold, treasuries and the dollar.
• Questions: how much to hedge, how expensive are the hedges, and how effective are the hedges?
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HEDGING OTHER BUSINESS DOWNTURNS
• Similar story. • Volatility, treasuries, gold and the
dollar rise as equities fall
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HEDGING INFLATION
• Hedge with commodities, real estate, equities, volatility, TIPS.
• We have not had serious inflation for decades so must rely on theory rather than empirical performance.
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HEDGING GLOBAL WARMING
• Hedge with companies expected to do well in a new low carbon environment. This could be alternative energy strategies, non-carbon transportation and manufacturing solutions, etc.
• Are investors doing this hedge? Probably, as these stocks traditionally are expensive.
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HEDGING S&P WITH EMERGING MARKETS, GOLD, TREASURIES, OR VOLATILITY
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HEDGING WITH DOLLAR OR GOLD
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CONCLUSION
• Make sure you take only the risks you intend to take.
• Pay attention to long term risk as well as short term risks.
• Consider reducing exposure to long term risks by hedging.
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