CBOE Risk Management Conference Europe Beyond VIX: Trading Volatility and Variance Across Asset Classes

Chris Rodarte, Pine River Capital Management

October 2, 2013

Agenda

• Case for considering volatility products across other asset

classes

• Introducing a systematic trading framework to compare

hedges within a given asset class and across other assets

• Comparison of historic results between the systematic

approach and the CBOE S&P 500 PutWrite Index

• Revisiting the VIX and Volatility Indexes of other assets

• Tying everything together: What is the best hedge?

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Asset Correlations are at Extremes

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60.00%

80.00%

Historic Cross Asset Correlation (10Y Swaps, SPX, WTI, DXY)

3M X-Asset Correl

Russia Default/LTCM Collapse Lehman Bankruptcy

Flash Crash 2010

EU Debt Crisis

Gulf War Concerns

Fed Taper Talk

Source: Pine River, Bloomberg, BOAML

Impact of Asset Price Correlation

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• Post the 2008 Financial Crisis the market continues to exhibit new extremes in Asset Price Correlation

– Arguably the various Central Banks and their monetary policy actions and/or inactions are having a tremendous impact on market prices

– This is creating Risk On/Risk Off episodic cycles in the market and can lead to difficulty in managing portfolio risk

• Acknowledging this new paradigm and leveraging trading strategies to take advantage of this market phenomena can be beneficial

– Hedges that may not have been considered previously might be a better alternative now

– Implied correlation pricing parameters are also at highs

Portfolio Hedging Optimization

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• Choosing the best hedge is only half the battle – Comparison of SPX Puts, SPX Variance, CDX IG, and VIX

Futures illustrate different market regimes often favor one hedge over the others

– Using a standard methodology for managing these hedges highlights that over the long run there are clear standouts

• Using a target premium spend budget on a monthly basis that is rebalanced daily tends to outperform other less systematic hedging programs – A true hedge is not costless and therefore it is important to

capture profits on such hedges when the opportunity arises

– In periods of uncertainty, vol of vol is reasonably elevated and capturing this phenomena often yields better results than a more passive hedging program

Hedging Using a Constant Theta Cost

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SPX Option Theta over 30 Days Size Adjustment Given Implied Vol

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Implied Volatility

30D 95% Put 30D 90% Put 60D 95% Put

60D 90% Put 90D 95% Put 90D 90% Put

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15 17.5 20 22.5 25 27.5 30 32.5 35

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Implied Volatility

30D 95% Put 30D 90% Put 60D 95% Put

60D 90% Put 90D 95% Put 90D 90% Put

Source: Pine River

Systematic Hedging Example: S&P 500 in 2008

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30D 95% Put Position %Change 60D 95% Put Position %Change

90D 95% Put Position %Change 30DAY 95% Put Implied Vol

60DAY 95% Put Implied Vol 90DAY 95% Put Implied Vol

Source: Pine River,

Bloomberg

Rolling Put Hedge Comparison

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240.00NAV Short PutWrite (Monthly Rebalance) NAV 30DAY ATM Put (Daily Rebalance) SPX Index (RHS) CBOE PutWrite Index (RHS)

Source: Pine River,

Bloomberg

VIX and other Volatility Indexes

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• VIX is just the beginning – Utilizing the same VIX calculation methodology, the CBOE

has a number of additional Volatility Indexes to consider

– Several of these indices also have futures listed on them

– Of particular note are the OVX (CBOE Crude Oil ETF), GVZ (CBOE Gold ETF)

• Both Listed and OTC Variance is another consideration – Listed Variance trades primarily on the SPX (Bloomberg

ticker VAAA Index) and other launches are imminent

– OTC Variance trades across most Global Equity Indices, US Stocks, Global ETF’s, Currencies, Commodities, and occasionally other assets

• It is well established that VIX performance is negatively correlated to equity price returns but can the same be said about other Volatility Indexes?

VIX: Negatively Correlated to SPX with a Caveat

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y = -3.8137x + 0.0031 R² = 0.4961

y = 14.706x2 - 3.8147x + 0.0011 R² = 0.5067

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Daily Change SPX Source: Bloomberg

OVX: Somewhat Negatively Correlated to USO

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y = -0.7629x + 0.001 R² = 0.1355

y = 11.639x2 - 0.7324x - 0.005 R² = 0.2069

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Daily Change USO Source: Bloomberg

GVZ: Convexly Correlated to GLD?

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y = -0.5856x + 0.0017 R² = 0.0201

y = 43.17x2 - 0.5688x - 0.0066 R² = 0.2054

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Daily Change GLD Source: Bloomberg

Quiz Question: What is this Equity Index?

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y = -1.5551x + 0.0055 R² = 0.1984

y = 56.688x2 - 1.0727x - 0.0151 R² = 0.4802

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Source: Bloomberg

VIX vs V2X Historical Spot Spread Comparison

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Source: Bloomberg 0.00%,

50.00%,

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VIX vs V2X Volatility Surface Divergence

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501M 100% Call Vol Diff 1M 120% Call Vol Diff 1M 150% Call Vol Diff

Source: Bloomberg

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100.0% 102.5% 105.0% 110.0% 120.0% 150.0% 200.0% 300.0%

Oct-2013 Vol Diff Nov-2013 Vol Diff Dec-2013 Vol Diff Jan-2014 Vol Diff

What can we learn for these Volatility Indexes?

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• Owning volatility in variance format allows one to participate in both the Left and Right Tails

– Both OVX and GVZ illustrate option implied volatility can increase meaningfully when the price of their respective commodities not only decrease in value but also increase in value

– More recently, some Equity Indices have also exhibited a similar phenomena

• Volatility of Volatility on the VIX is consistently elevated relative to the V2X

• Using a constant theta systematic hedging approach outlined earlier we can compare how owning variance on these assets performed relative to other hedges

S&P 500 Hedge Performance Comparison

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NAV 30DAY 95.0% PUT NAV 30DAY 90.0% PUT NAV 60DAY 95.0% PUT NAV 60DAY 90.0% PUT

NAV 90DAY95.0% PUT NAV 90DAY 90.0% PUT NAV 30DAY VAR NAV 90DAY VARSource: Pine River,

Bloomberg

Realized Volatility Comparison Across Assets

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100.00%SPX 3M Rvol GOLD 3M Rvol WTI 3M Rvol LDQ 3M Rvol HYG 3M Rvol

Source: Pine River, Bloomberg

Hedge Performance Comparison across Assets

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Source: Pine River,

Bloomberg 40

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NAV 30DAY SPX VAR NAV 90DAY SPX VAR NAV 30DAY WTI VAR NAV 90DAY WTI VAR

NAV 30DAY GOLD VAR NAV CDX IG 5Y PROT NAV 30D VIX FUTS

Hedge Results Summary

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YEAR

30DAY

95.0%

SPX PUT

30DAY

90.0%

SPX PUT

60DAY

95.0%

SPX PUT

60DAY

90.0%

SPX PUT

90DAY

95.0%

SPX PUT

90DAY

90.0%

SPX PUT

30DAY

SPX VAR

90DAY

SPX VAR

30DAY

WTI VAR

90DAY

WTI VAR

30DAY

GOLD VAR

CDX IG

5Y PROT

30DAY

VIX FUTS

2006 -9.35% -14.52% -6.39% -3.35% -9.15% -4.37% -11.29% -9.83% 4.04% 3.31% -6.01% -25.49% -3.35%

2007 11.07% 16.10% 8.17% 10.97% 9.92% 11.35% 5.36% 12.38% -0.20% 6.01% 0.37% 36.39% 3.19%

2008 20.52% 28.26% 26.62% 23.78% 36.89% 30.96% 18.97% 31.45% 17.51% 39.38% 10.52% 75.39% 5.17%

2009 -8.44% -9.40% -10.53% -8.24% -12.73% -9.98% -12.46% -13.67% -9.21% -8.28% -18.58% -48.69% -5.08%

2010 -6.11% -7.16% -7.40% -4.92% -10.36% -7.04% -11.94% -13.64% -11.47% -11.54% -17.63% -9.79% -6.44%

2011 3.06% 3.98% 3.03% 3.99% 2.73% 3.83% 2.38% 3.48% -1.40% 3.59% -6.20% 11.30% 1.43%

2012 -11.48% -16.55% -11.03% -8.63% -14.78% -11.02% -18.49% -30.47% -15.68% -14.73% -13.60% -28.95% -7.61%

2013 -9.16% -11.44% -9.67% -6.50% -14.00% -9.44% -10.84% -18.26% -8.03% -6.32% 27.32% -17.33% -3.35%

Average* -0.96% -1.00% -0.60% 1.14% -1.01% 0.87% -4.58% -4.36% -2.89% 1.69% -4.01% -0.34% -1.96%

Best 20.52% 28.26% 26.62% 23.78% 36.89% 30.96% 18.97% 31.45% 17.51% 39.38% 27.32% 75.39% 5.17%

Worst -11.48% -16.55% -11.03% -8.63% -14.78% -11.02% -18.49% -30.47% -15.68% -14.73% -18.58% -48.69% -7.61%

Ratio 1.79 1.71 2.41 2.76 2.50 2.81 1.03 1.03 1.12 2.67 1.47 1.55 0.68

Source: Pine River,

Bloomberg

Note: Average is weighted through to September 2013

Conclusions

• Asset prices and their underlying volatilities have exhibited

increased correlation especially during periods of distress

• Given a standardized systematic approach to hedging one

can compare how different hedges performed over a given

period of time

• Not surprisingly, different hedges work better over different

periods of time and dislocations in one market segment

often lead to dislocations in the broader market

• Rotating some portion of your hedge dynamically across a

subset of highly correlated assets can improve performance

and/or reduce the long run cost of buying protection

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