Investing in Volatility Strategies An Introduction CAIA Educational Event Zürich, 3rd of December 2013 Dr. Daniel Hofstetter
Table of Contents Investing in Volatility Strategies - An Introduction The term «Volatility» Established tradable Instruments Characteristics of Volatility Common Volatility Strategies Opportunities for Volatility Strategies Challenges Summary 2
The term «Volatility» General information Latin: Volatilis - flying/volatile In general a measurement for the fluctuation of a certain parameter Financial and capital markets Measurement for the fluctuation of financial parameters (prices, interest rates, etc.) Defined as standard deviation Serves for the assessment of risk (risk measure) Historic or realized volatility Standard deviation of time series from financial parameters Mostly used regarding rates of return Ex post calculation Implied volatility Derived from market prices of options on underlying assets Standard deviation of the underlying rate of return (random variable) contained in option prices implied Ex ante measurement that reflects the current expected variation of the base value Depending on the option pricing model 2013 IFR Institute for Financial Research 3
The term «Volatility» 106 104 Current implied Volatility 102 Investment Value 98 Historic/realized Volatility Future implied Volatility 96 94 Past Today Future 92 2013 IFR Institute for Financial Research 4
Established tradable instruments Futures on implied volatility Futures on the implied volatility that captures the 30 days forward looking implied volatility on the futures expiration date (standardized p.a.) Implied volatility reflects the standard deviation of the underlying rate of returns (random variable) contained in option prices implied Markets: S&P 500/VIX, STOXX 50/VSTOXX, NIKKEI 225/VNKY VIX index Currently embedded 30 day implied volatility in S&P 500 options (standardized p.a.) Non tradable Further instruments (implied vs. realized volatility) Variance Swap Delta neutral short option portfolio 5
Characteristics of Volatility Development Daily Data 300 260 220 Source: Bloomberg, own Calculations 240 220 200 180 Characteristics of implied volatility Strong negative correlation with stocks Value (USD/lhs) 180 140 60 20-20 160 140 120 80 60 40 20 Implied Volatility (%/rhs) Mostly low implied volatility during positive stock markets periods Negative to very low correlation with commodities and bonds -60 0 Persistent characteristics Correlation 1.00 0.75 0.50 0.25 0.00-0.25-0.50-0.75-1.00 S&P 500 TR (lhs) S&P 500 VIX Mid-Term Futures Index TR (lhs) VIX Index (rhs) Rolling Correlations (3 Months // USD) Daily Data Source: Bloomberg, own Calculations Comment S&P 500 VIX Mid-Term Futures Index TR: Investable Same roll mechanism as for the well known VIX-ETN of ipath (VXX, VXZ, ) Correlation characteristics with stocks, commodities and bond also consistent with investable VIX Futures implementations (instead of VIX Index) VIX Index vs. S&P 500 TR VIX Index vs. JPM Global Aggregate Index VIX Index vs. DJ UBS Commodity TR Index 6
Characteristics of Volatility Development Daily Data Further characteristics of implied volatility Value (USD/lhs) 350 300 250 200 150 50 0 Source: Bloomberg, own Calculations 220 200 180 160 140 120 80 60 Implied Volatility (%/rhs) Sudden spikes In connection with stock market crashes Typically high in magnitude Grey ellipses Mean reverting -50-40 20 Normalization over a determined period of time -150 0 Persistent characteristics S&P 500 VIX Short-Term Futures Index TR (lhs) VIX Index (rhs) S&P 500 VIX Mid-Term Futures Index TR (lhs) VIX Futures 1st Contract (rhs) Comment S&P 500 VIX Short or Mid-Term Futures Index TR: Investable Same roll mechanism as for the well known VIX-ETN of ipath (VXX, VXZ, ) 7
Characteristics of Volatility Contango and Backwardation 35 Characteristics of the futures curve Futures Price (%/implied Volatility) 30 25 20 High Fluctuation Backwardation Low Fluctuation Contango Mainly in contango Usually generating rollover losses Variations significantly bigger at the short end than at the long end 15 10 0 1 2 3 4 5 6 Contract Development of Contango and Backwardation Daily Data 8 0 Difference (%-Points) -8-16 -24-32 Source: Bloomberg, own Calculations Difference (VIX Futures 2nd Contract minus VIX Futures 1st Contract) Difference (VIX Futures 6th Contract minus VIX Futures 1st Contract) 8
Characteristics of Volatility Volatility (%) 90 80 70 60 50 40 30 Implied Volatility vs. realized Volatility Daily Data Source: Bloomberg, own Calculations Characteristics of implied vs. realized volatility Implied volatility generally higher than realized volatility Inversion combined with spikes 20 10 0 VIX Index (shifted by 30 days) S&P 500 TR 9
Common Volatility Strategies 1. Hedging of Stock Positions with Volatility Futures Target Hedging of stock positions Benefit from the strong negative correlation between implied volatility of stocks and stocks itself Mechanism Buying of implied volatility via futures Partially including a signal for exposure adjustments S&P 500, STOXX 50, NIKKEI 225, Challenge Over long periods high rollover costs for futures ( see next slide) Comments Emerged after stock market crash in 2008 Known implementation: ETF «VXX US» (ipath S&P 500 VIX Short-Term Futures ETN) 2013 IFR Institute for Financial Research 10
Common Volatility Strategies 120 80 Development Daily Data Source: Bloomberg, own Calculations Challenge of pure hedging strategies Simple long VIX futures strategies High rollover costs over longer periods Value (USD) 60 40 20 0-20 Comment ipath S&P 500 VIX Short-Term Futures ETN Passive ETN on long short-term VIX futures Also known as VXX US ipath S&P 500 VIX Short-Term Futures ETN (VXX) VIX Investment 1st Contract S&P 500 VIX Mid-Term Futures Index TR S&P 500 VIX Mid-Term Futures Index TR Investable Same roll mechanism as for the well known VIX-ETN of ipath (VXX, VXZ, ) 11
Common Volatility Strategies 2. Carry Strategy Target Capitalize on primarily negative rollover effects Collecting carry Mechanism Selling of implied volatility via futures Partially including a signal for exposure adjustments S&P 500, STOXX 50, NIKKEI 225, Challenge Risk of spikes in implied volatility Increasing price of futures contract Losses due to the repurchase (unwind) of the futures contract Ongoing small earnings are suddenly facing great losses Comments Other side (short side) in trading implied volatility futures 2013 IFR Institute for Financial Research 12
Common Volatility Strategies 3. Combination Strategy (Combination of Hedging and Carry) Target Linking the advantage of Hedging (protection) and Carry (current earnings) Mitigation of respective problems Hedging (rollover costs) and carry (implied volatility spikes) Mechanism Adjustment of weights whether to force hedging or carry techniques Decision based on signals/algorithms Buying and selling of implied volatility via futures S&P 500, STOXX 50, NIKKEI 225, Challenge Product diversity Different levels of maturity regarding mechanisms Comments Example of signals Shape of the futures curve Volatility of volatility Momentum of volatility etc. 2013 IFR Institute for Financial Research 13
Common Volatility Strategies 4. Risk premium strategy Target Capitalize on primarily positive premiums between implied vs. realized volatility Collecting risk premiums Mechanism Basically selling of implied volatility and buying of realized volatility Variants A: Short selling of options and regular delta hedging B: Selling of Variance SWAP S&P 500, STOXX 50, NIKKEI 225,... Challenge Risk of spikes in realized volatility Cost increases in realized volatility Delta Hedging costs more (Variant A) Variance Swap becomes more expensive (Variant B) Normally, mitigate risk by weight adjustment based on signals/algorithms High (Low) spike potential triggers an exposure reduction (increase) Comments Mostly lower risk compared to combination strategies Example of a signal: recent realized volatility vs. implied volatility 2013 IFR Institute for Financial Research 14
Common Volatility Strategies Comment Strategy Combi A and B: Common implementations for combination strategies Strategy Risk Premium A and B: Common implementations for risk premium strategies 15
Value (USD) Drawdown (%) 1'800 1'600 1'400 1'200 1'000 800 600 400 200 0 0-10 -20-30 -40-50 Common Volatility Strategies Return Comparison of Example Strategies Weekly Data Different inital values, hence the same scale can be used Strategy Combi A Strategy Combi B Strategy Risk Premium A Strategy Risk Premium B Drawdown Example Strategies (USD) Weekly Data Source: Bloomberg, Provider, PackHedge, own Calculations Source: Bloomberg, Provider, PackHedge, own Calculations Characteristics of the strategies High return potential throughout different market periods Mean reverting around a positive Trend Partially not correlated with each other Mostly not correlated with traditional investments Drawdowns can be large Conclusion Existence of different and diverse volatility strategies No clear definition of a volatility investment Diversification across a variety of strategies/ sources of return is appropriate Useful diversification to a traditional portfolio Strategy Combi A Strategy Combi B Strategy Risk Premium A Strategy Risk Premium B 16
Opportunities for Volatility Strategies Value (USD) 160 150 140 130 120 110 90 Extension (Backtesting) Weekley Data Extension of a balanced mandate with a volatility portfolio Positive influence on the balanced portfolio across different market periods Reduced drawdowns as in 2008 Better performance Value (USD) 80 200 180 160 140 120 80 60 40 Source: Bloomberg, Provider, PackHedge, own Calculations Balanced international incl. 10% Vola-Portfolio (general / backtesting / net) Balanced international 40/60 Comparison to traditional Asset Classes (Backtesting) Weekly Data Different inital values, hence the same scale can be used Source: Bloomberg, Provider, PackHedge, own Calculations Portfolio Volatility (general / backtesting / net) JPM Global Aggregated Bond Index MSCI AC World DJ-UBS Commodity Index Comparison with traditional asset categories Return potential High during different market periods Especially high in long lasting negative stock markets Mostly uncorrelated Low drawdowns ------------------------------------------------------------------ Explanation Portfolio «Balanced international 40/60» 40% stocks world / 60% bonds world Volatility Portfolio (backtesting) General strategy selection, not optimized, lack of RM Net of fees: Includes fees of particular strategies, but no further costs 17
Value (USD) Value (USD) 320 300 280 260 240 220 200 180 160 140 120 80 320 300 280 260 240 220 200 180 160 140 120 80 Challenges Source: Bloomberg, Provider, PackHedge, own Calculations Example: Single Focus Weekly Data Charts shown only upon request Source: Bloomberg, Provider, PackHedge, own Calculations Week Example Strategy A Example: Single Focus Weekly Data Week Example Strategy A Challenges Many similar strategies Normally, the backtesting is very good Risk management mechanisms or allocation signals are partly missing Partly single focus on a particular market period Answer see slide after next slide Example: Single focus (charts) Upper chart Strategy yields good results during spikes (grey ellipses) Lower chart Initially confirmation of expectation (good covering of spikes First 50 weeks of green line) Overall weak after spikes (grey ellipses) Especially after week 261 Focus not enough diversified 18
Challenges Example: Changing Market Environment Weekly Data 700 600 Source: Bloomberg, Provider, PackHedge, own Calculations Charts shown only upon request Challenges (cont.) 500 Even mature programs can face difficulties Value (USD) 400 300 Answer see next slide 200 Example: Changing market environment (charts) Value (USD/lhs) 0-700 600 500 400 300 200 Week Example Strategy B Example: Changing Market Environment Weekly Data Source: Bloomberg, Provider, PackHedge, own Calculations 120 110 90 80 70 60 50 40 Implied Volatility (%/rhs) Upper chart Accumulation of large drawdowns (-12% and higher) and fast recoveries (grey ellipse) Even stronger on a daily basis Lower chart Explanation: VIX Index for a long time below 18% Higher percentage change of VIX per one unit of volatility (grey ellipse) Consequence: Modification of strategy allocation mechanism by the manager 30 0 20 10-0 Week Example Strategy B (lhs) VIX Index (rhs) 19
Challenges - Answers Severe Selection of the Strategies Controlling of Market Environment Crucial Elements for a Volatility Portfolio Focus on Allocation Mechanism Proper Risk Management of the Strategies Diversification across several Strategies 20
Summary Summary Interesting, own asset category High potential as a diversifying source of return No clear investment in volatility but several volatility sources of return Volatility strategies with pros and cons Essential for investing in volatility strategies is Selection of strategies Sound analyses of allocation mechanism Diversification Proper risk management Controlling of market environment Contact Dr. Daniel Hofstetter, Institute for Financial Research AG IFR, Neugasse 55, 9000 St. Gallen +41 71 243 05 03, daniel.hofstetter@ifr-assetmanagement.com 21
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