Trading Volatility: Theory and Practice Presented by: Eric Metz, CFA FPA of Illinois Conference for Advanced Planning October 7, 2014 Trading Volatility: Theory and Practice Institutional Use Only 1
Table of Contents I. Introduction to Options and Volatility II. Volatility as an Asset Class III. Trading Volatility IV. Investment Strategies Using Options V. Incorporating Volatility Strategies in Portfolios Trading Volatility: Theory and Practice Institutional Use Only 2
I. Introduction to Options and Volatility Trading Volatility: Theory and Practice Institutional Use Only 3
Introduction to Options and Volatility Options are important for multiple reasons: 1. When used appropriately, options have the potential to enhance risk-adjusted returns by increasing portfolio returns and/or reducing portfolio volatility. 2. Options are flexible tools that can help define potential portfolio risk and return. 3. Options can be used to hedge individual security or overall portfolio risk. Trading Volatility: Theory and Practice Institutional Use Only 4
Introduction to Options and Volatility Volatility as an Alternative to Equities and Fixed Income Potential Benefits of a Volatility Strategy Market Scenarios: Possible Strategy Outcomes Risk- Management High correlation to the equity markets with lower volatility than the S&P 500 Index Contrarian Benefit The strategy enables investors to buy stocks when markets are falling and sell stocks when markets are rallying Alternative Unique source of alpha generation from trading options and an alternative investment strategy in a mutual fund structure Volatility strategies can have equity-like characteristics in the form of high correlation to broad equity markets and bond-like characteristics in the form of low volatility. Trading Volatility: Theory and Practice Institutional Use Only 5
Introduction to Options and Volatility Why Volatility Strategies Now? Equity markets have rallied more than 220% since March 2009 * Equity markets have rallied more than 90% since August 2011 ** Interest rates and credit spreads are near historic lows Due to the prospect of low future returns, pensions, endowments and retirees will need alternatives as a result of the allocation away from traditional fixed income and equity strategies. * Indicates S&P 500 Index Total Return of 221.3069% from 3/1/2009 through 8/31/2014 ** Indicates S&P 500 Index Total Return of 90.432% from 8/19/2011 through 8/31/2014 Trading Volatility: Theory and Practice Institutional Use Only 6
Introduction to Options and Volatility Volume (Millions) 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012 Volume (Millions) Options Volume: An Increase Over the Years Annual Options Volume Average Daily Options Volume Total Options Volume Avg Daily Total Options Volume 5,000 20 4,500 18 4,000 16 3,500 14 3,000 12 2,500 10 2,000 8 1,500 6 1,000 4 500 2 0 0 Data as of 8/31/2014. Source: Options Clearing Corporation Trading Volatility: Theory and Practice Institutional Use Only 7
Introduction to Options and Volatility A nnualized Percent Return / St dev Goldman Sachs Study on Mutual Fund Use of Options 5 year return and standard deviation 16.0 15.5 15.0 14.5 Higher returns and lower volatility led to higher risk adjusted returns 1.05 1.00 0.95 14.0 Total Return Options users Peers by objective Standard Deviation Risk adjusted return 0.90 Definitions: Option user a mutual fund that uses any type of options in its portfolio; can be used for alpha generation or risk mitigation. Peers by Objective mutual funds in the same peer group that do not use any type of options or options strategies. Study published by Goldman Sachs Global Investment Research, March 2014. Source: SEC filings, Strategic Insight, data as of March 4, 2014. Trading Volatility: Theory and Practice Institutional Use Only 8
Introduction to Options and Volatility Average AUM ($bil) 3/09 6/09 9/09 12/09 3/10 6/10 9/10 12/10 3/11 6/11 9/11 12/11 3/12 6/12 9/12 12/12 3/13 6/13 9/13 12/13 Goldman Sachs Study on Mutual Fund Use of Options Mutual funds that use options tend to be larger than peers and have attracted more assets in recent years. 6 5 Options users have grown assets 160% in the past 5 years vs their peers by objective up 110%. 4 3 2 1 0 Options users Peers of options users (by objective) Definitions: Option user a mutual fund that uses any type of options in its portfolio. Can be used for alpha generation or risk mitigation. Peers of options user mutual funds in the same peer group that do not use any type of options or options strategies. Study published by Goldman Sachs Global Investment Research, March 2014. Source: SEC filings, Strategic Insight, data as of March 4, 2014 Trading Volatility: Theory and Practice Institutional Use Only 9
II. Volatility as an Asset Class Trading Volatility: Theory and Practice Institutional Use Only 10
Volatility as an Asset Class Why Volatility should be considered an Asset Class: Volatility is investable and tradable. Volatility has its own set of risk and return characteristics. Volatility behaves differently than other mainstream asset classes. Volatility is non-correlated (different from negatively correlated). 11 Trading Volatility: Theory and Practice Institutional Use Only 11
III. Trading Volatility Trading Volatility: Theory and Practice Institutional Use Only 12
Trading Volatility Investment Opportunity Defined: The market price of a listed option is ultimately a function of the supply and demand for the specific option within an underlying security and the interplay of the two forces will change the implied volatility 1 of an option s price. Supply and demand imbalances may cause the implied volatility to diverge from the security s inherent volatility, resulting in a potential profit opportunity. An option s market price is determined by 5 input variables: 1. Underlying stock price 2. Strike price 3. Interest Rates/Dividends 4. Time to expiration 5. Implied volatility Trading Volatility: Theory and Practice Institutional Use Only 13
Trading Volatility Option Trading in Practice When future volatility differs significantly from the market s estimate of future volatility, a trading opportunity arises. Important to construct a portfolio of options based on volatility mispricing while also actively managing overall portfolio beta. XYZ Trade Example Implied Volatility Difference (XYZ - SPX) 8/31/2005-8/31/2014 During the 2008 financial crisis, the implied volatility for hypothetical company XYZ was expensive versus an estimate of realized volatility 2 In addition, the implied volatility of XYZ was expensive versus the implied volatility of the S&P 500 Index Decision Individual name (XYZ) is attractive v. SPX => Sell XYZ Call to capture collapsing premium 30 25 20 15 10 5 0-5 -10-15 1 Implied Vol Difference (XYZ - SPX) Past performance does not guarantee future results. XYZ-SPX Imp = Difference between XYZ Implied Volatility and S&P 500 Implied Volatility Source: Bloomberg, RiverNorth Capital Management, LLC Trading Volatility: Theory and Practice Institutional Use Only 14
Trading Volatility Volatility Volatility is Tradable Implied volatility varies between strike price, maturity, sector and asset class, presenting a different opportunity set for each option. Spreads between implied and realized volatility can be successfully traded or captured, often referred to as volatility arbitrage. When pricing options, all variables are directly measurable except for volatility it is an estimate. When a security s implied volatility diverges from RiverNorth s estimate of future volatility, a potential mispricing arises. Correctly identifying and capitalizing on volatility mispricing provides a source of return relatively independent of general market direction. The chart below is evidence that realized (or actual) volatility is typically lower than implied volatility. 80 SPX Implied & Realized Volatility: 8/31/2005 8/31/2014 70 60 50 40 30 20 10 0 60 Day Implied Vol Realized Vol Source: Bloomberg Trading Volatility: Theory and Practice Institutional Use Only 15
Trading Volatility Implied and Realized Volatility (60-day call option on SPY) 40 Realized Vol Average Implied Vol Average Difference 35 30 25 20 15 10 5 0-5 2005 2006 2007 2008 2009 2010 2011 2012 2013-10 Sources: Bloomberg, RiverNorth Capital Management, LLC Trading Volatility: Theory and Practice Institutional Use Only 16
Trading Volatility Million Dollar Question: Long or Short Volatility? Short Volatility Holds a negative connotation and is often misunderstood. Elicits fear of unlimited loss potential, but loss potential is greatly influenced by how much leverage is deployed. Leverage ratio of the investor s portfolio will dictate true exposure to any investment, although it is amplified in volatility strategies because of convexity 3 (positive & negative). Long Volatility Attractive convex payouts and portfolio protection, which can be viewed as lottery tickets. Both short and long volatility strategies have a time and a place. Assessing when to allocate to each strategy depends on the investor s needs, but most importantly, the investor s time horizon and objective. Trading Volatility: Theory and Practice Institutional Use Only 17
Trading Volatility Aggregate P/L generated by selling $10k vega 4 worth of 1m SPX variance every trading day (spot VIX 5 is used to approximate the level of 1m variance). $ Source: Macro Risk Advisors Trading Volatility: Theory and Practice Institutional Use Only 18
IV. Investment Strategies Using Options Trading Volatility: Theory and Practice Institutional Use Only 19
Investment Strategies Using Options Common Approaches to Options Trading A variety of option strategies are available to obtain the optimal risk-reward profile given the opportunity in the marketplace: Buy-Write Collar Long Call-Spread & Short Put Calendar Spreads (Put and Call) Risk Reversal Each strategy has merit, but opportunistically shifting exposure among the various strategies as market conditions vary will potentially deliver superior risk-adjusted returns over time. Trading Volatility: Theory and Practice Institutional Use Only 20
Investment Strategies Using Options Buy-Write (Covered Call, Cash-Secured Put) Long stock, and short at-the-money or slightly out-of-the-money, call to provide income enhancement and lower return volatility vs. long stock portfolio Buy-Write will outperform long stock portfolio in sideways, down, and slightly up markets Buy-Write will underperform in strong, persistent market rallies with few pullbacks Buy-Write Performance At Option Expiration 25% 20% 15% 10% 5% 0% -5% -10% -15% -20% -25% -20% -15% -10% -5% 0% 5% 10% 15% 20% Long Stock ATM Buy-Write Trading Volatility: Theory and Practice Institutional Use Only 21
Investment Strategies Using Options Collar Long stock, short out-of-the-money call and long out-of-the-money put Collar strategy will outperform long stock portfolio in down markets due to long put performance contribution; cost of downside protection is reduced by sale of upside call Collar strategy will underperform in strong, persistent market rallies with few pullbacks 25% 20% 15% 10% Collar Strategy Performance At Option Expiration 5% 0% -5% -10% -15% -20% -25% -20% -15% -10% -5% 0% 5% 10% 15% 20% Long Stock 5% OTM Collar Trading Volatility: Theory and Practice Institutional Use Only 22
Investment Strategies Using Options Long Call Spread, Short Put ( 3-Way ) Long at-the-money call, short out-of-the-money call and short out-of-the-money put often zerocost Long call spread, short put strategy will perform comparable to long stock portfolio in minor rallies and will outperform in market sell-offs Long call spread, short put strategy will underperform a long stock portfolio in significant market rallies 25% 20% 15% 10% Long Call Spread, Short Put Strategy Performance At Option Expiration 5% 0% -5% -10% -15% -20% -25% -20% -15% -10% -5% 0% 5% 10% 15% 20% Long Stock Long Call Spread, Short Put Trading Volatility: Theory and Practice Institutional Use Only 23
Investment Strategies Using Options Call Calendar Spread Short out-of-the-money call in near-term expiration, long out-of-the-money call with same strike that expires at a later date beyond the first option s expiration Calendar spreads provide a method to take advantage of the expiration term structure present in the options marketplace either long or short while getting paid to wait 25% 20% 15% 10% Call Calendar Spread Strategy Performance At First Option Expiration 5% 0% -5% -10% -15% -20% -25% -20% -15% -10% -5% 0% 5% 10% 15% 20% Long Stock Call Calendar Trading Volatility: Theory and Practice Institutional Use Only 24
Investment Strategies Using Options Risk Reversal Long out-of-the-money call, short out-of-the-money put Risk Reversal strategy provides an advantageous method to gain long / short exposure to a security because of the implied volatility skew structure present in the options marketplace 25% 20% 15% 10% Risk Reversal Strategy Performance At Option Expiration 5% 0% -5% -10% -15% -20% -25% -20% -15% -10% -5% 0% 5% 10% 15% 20% Long Stock 5% OTM Risk Reversal Trading Volatility: Theory and Practice Institutional Use Only 25
Investment Strategies Using Options CBOE Benchmark Indices Defined PUT, BXM, CLL PUT Index The CBOE S&P 500 PutWrite Index, measures the performance of a hypothetical portfolio that sells S&P 500 Index (SPX) put options against collateralized cash reserves held in a money market account. BXM Index The CBOE S&P 500 Buy-Write Index (BXM) is a benchmark index designed to track the performance of a hypothetical buy-write strategy on the S&P 500 Index. CLL Index The CBOE S&P 500 95-110 Collar Index is a passive collar strategy that entails holding the stocks in the S&P 500 Index; buying three-month S&P 500 put options to protect this S&P 500 portfolio from market decreases; and selling one month S&P 500 call options to help finance the cost of the puts. Trading Volatility: Theory and Practice Institutional Use Only 26
Investment Strategies Using Options BXM Monthly Call Premiums as a % of Notional Exposure 9.00% 8.00% 7.00% Call Premium As % of Notional Exposure Average 6.00% 5.00% 4.00% 3.00% 2.00% 1.00% 0.00% Jan-04 May-05 Sep-06 Feb-08 Jun-09 Nov-10 Mar-12 Aug-13 Dec-14 Source: CBOE BXM call premiums sold averaged about 1.8% per month. Consequently, on average, the BXM should usually outperform the S&P 500 in any expiration month that returned less than 1.80%. * Please note that these are gross amounts, and the net return usually will be less with a Buy-Write strategy. Trading Volatility: Theory and Practice Institutional Use Only 27
Investment Strategies Using Options Equity Option Indices Overall Performance vs. SPX Over multiple market cycles, options-based strategies have delivered better risk-adjusted returns than equity portfolios (i.e., S&P 500) as measured by the Sharpe Ratio 6. % of Time Index Outperforms SPX Sharpe (1990 2014 H1) 1 Year Rolling 3 Year Rolling 5 Year Rolling 10 Year Rolling PUT 55.70% 63.60% 75.01% 79.33% BXM 42.95% 42.35% 54.06% 70.50% Source: Bloomberg Trading Volatility: Theory and Practice Institutional Use Only 28
V. Incorporating Volatility Strategies in Portfolios Trading Volatility: Theory and Practice Institutional Use Only 29
Incorporating Volatility Strategies in Portfolios Benefits to Outsourcing Volatility Management Utilizing multiple combinations of volatility strategies can help reduce overall portfolio risk and/or improve portfolio return. Combining several options strategies in a portfolio creates new risk/reward profiles that should be monitored and monetized. Monetizing alpha is difficult, cumbersome and requires professional execution. Exposure to the asset class (volatility long and/or short) can be a strategic or tactical decision. Incorporating the asset class may add diversification to the portfolio. 30 Trading Volatility: Theory and Practice Institutional Use Only 30
Incorporating Volatility Strategies in Portfolios Considering Managed Volatility in a Portfolio Allocation Where Do These Strategies Fit? Who Should Consider These Strategies? Within portfolios to: Investors looking for: 1) Complement an existing broad equity market exposure 2) Diversify an alternative investments allocation 1) Lower volatility equity portfolio relative to the S&P 500 Index 2) A unique alpha source 3) Lower beta exposure to the equity markets 4) Liquid alternative to strategy traditionally offered in LP form Trading Volatility: Theory and Practice Institutional Use Only 31
Portfolio Manager Biography Eric Metz, CFA - Portfolio Manager, RiverNorth Eric Metz is a portfolio manager and derivatives strategist at RiverNorth Capital Management, LLC. Eric aids the firm in optimizing the risk management across its portfolios while managing the derivatives oriented portfolios. Eric has been a guest lecturer at the Ross School of Business of the University of Michigan on the rising and prolific use of options and derivatives as strategic investment tools, and viewing volatility as an asset-class. Prior to joining RiverNorth, Eric was a partner at Bengal Capital LLC, a privately owned Chicago-based hedge strategy. Eric has traded derivatives on various asset classes on the floors of the CBOE, CME and electronically since 2003. Prior to Bengal, Eric was a senior trader at Ronin Capital, LLC, a privately owned hedge fund and the Chicago Trading Company, a privately owned quantitative derivatives firm. Eric graduated Magna Cum Laude from the University of Michigan with a B.S.E in Industrial and Operations Engineering. He then earned his M.S.E., with honors, in Industrial and Operations Engineering from the University of Michigan. He was enrolled in the Industrial and Operations Engineering PhD program at the University of Michigan before pursuing his career path. He also has received the Chartered Financial Analyst (CFA) designation, is a member of both the CFA Institute and the CFA Society of Chicago. Trading Volatility: Theory and Practice Institutional Use Only 32
Disclosures 1. Implied Volatility is the volatility that is being implied by the options in the marketplace over a given time period. 2. Realized Volatility is the calculated volatility of a financial instrument over a given time period with the latest observation usually being the last observable observation. 3. Convexity is a measure of the curvature in the relationship between option prices and underlying security prices. Convexity is used as a risk-management tool and helps to measure and manage the amount of market risk to which a portfolio of bonds is exposed. 4. Vega is the measurement of an option s sensitivity to changes in the volatility of the underlying asset. 5. The CBOE Volatility Index (VIX) is a key measure of market expectations of near-term volatility conveyed by S&P 500 stock index option prices. Since its introduction in 1993, VIX has been considered by many to be the world s premier barometer of investor sentiment and market volatility. 6. Sharpe Ratio is the rate of return of a portfolio divided by the standard deviation of it s returns minus the risk-free rate Options are not suitable for all investors, and trading in these instruments is considered risky and may be appropriate only for sophisticated investors. Past performance is not necessarily indicative of future results. Various theoretical explanations of the risks associated with these instruments have been published. Prior to buying or selling an option, and for the complete risks relating to options, you must receive a copy of The Characteristics and Risks of Standardized Options. You may read the document at http://www.optionsclearing.com/about/publications/character-risks.jsp. 33 Trading Volatility: Theory and Practice Institutional Use Only 33