Investing In Volatility By: Anish Parvataneni, CFA Portfolio Manager LJM Partners Ltd. LJM Partners, Ltd. is issuing a series a white papers on the subject of investing in volatility as an asset class. These papers will discuss the performance characteristics of short volatility as well as present specific trading strategies and associated risk management techniques. This is the first paper of the LJM series. Superior Returns for the Patient Investor
The incorporation of volatility strategies within traditional equity and bond portfolios is recognized as an effective method to increase portfolio returns while simultaneously reducing portfolio volatility. The objective of this paper is to define volatility as its own asset class, provide an overview of the characteristics of volatility investments, and to highlight the benefits of actively managed volatility portfolios.
Defining Volatility Volatility of an investment is defined as the standard deviation of its returns over a certain period of time. Volatility is widely considered the primary measure of risk of an investment. Therefore, the goal for any well constructed investment portfolio is to reduce performance volatility relative to the targeted rate of return. There are several different measures of volatility including implied volatility, realized volatility, and VIX, which is the short form of a volatility index published by the CBOE Futures Exchange ( CFE ). Implied volatility is a measure that is derived from option prices. Theoretical option prices themselves can be derived as a function of price of the underlying asset, time to expiry for an option, volatility of the underlying asset, and interest rates. Options are traded in the market through the process of price discovery. Several factors drive the price for an option including time to expiration, strike, interest rates and implied volatility. Typically, the value for implied volatility is derived using the classic Black Scholes Model and reflects the market forecast about the future. Conversely, realized volatility is based on historical data and is defined as the standard deviation of the underlying returns. Therefore, realized volatility is just a mathematical observation of how volatile the market has been historically. The analyses presented in this paper are based on the S&P 500 Index, which broadly represents the US equity market, and its associated volatility. VIX, the short form volatility index published by the CBOE Futures Exchange (CFE), represents the 30 day implied volatility of the S&P 500 Index. VIX is derived from prices of put and call options of different strikes and maturities. All of the analyses presented in this paper use VIX as the proxy for implied volatility. Characteristics of Volatility (VIX) Volatility does not produce dividends or interest; there is no passive income to be obtained by being long VIX. A noteworthy characteristic of VIX is its strong mean-reverting tendency. Over time VIX levels have a propensity to gravitate towards their long-term averages. Figure 1 displays the meanreversion of VIX over a 12 year period. In addition to mean-reversion, it is important to note that because the price of any option cannot fall below zero, VIX has a floor. Additionally, VIX has historically been negatively correlated to the S&P 500 Index. As the index moves lower, VIX moves higher and vice versa. The peak of VIX occurred during the market crash of 2008. (Figure 2) Figure 1: Mean-reversion of VIX VIX MEAN Figure 2: VIX s peak VIX SPX S&P 500 Index VIX
Investing In Volatility 2 Potential benefits of Investing in Volatility-Based Strategies Volatility based investment strategies can act as an effective diversifier in a broad based portfolio. The primary reason is that volatility itself is not a variable used in determining the current price of the underlying asset. Volatility represents the variability of the asset moving forward over a certain period of time. As time passes, the price of the underlying asset changes due to market factors that affect its supply and demand. Investors can go long or short the forward variability of an underlying asset using products that are priced using underlying market volatility expectations over a defined period of time. Since the volatility of returns of an asset can behave independently of the asset itself, opportunities exist to diversify a portfolio by investing across both an asset and its associated volatility. Market expectations about future volatility are reflected in the prices of options. There is also an element of practical loss aversion that affects the price of volatility-based assets such as options. For example, the downside protection offered by put option contracts is reflected in higher values for these contracts than the upside protection offered by equivalent call option contracts. Sellers of put option contracts can therefore capture this premium and realize systematic returns similar to classic insurance companies. Thus, the volatility implied by the prices of these options varies for put or call options that expire on the same maturity. Implied volatilities are often higher than the historical asset volatility reflecting a utility premium for the price protection which options offer. Volatility strategies themselves are generally uncorrelated to underlying assets for two primary reasons. First, the volatility of future price movements is uncorrelated to the current price of the underlying asset. Secondly, the expected volatility of the asset does not factor into the current price of the underlying asset. These characteristics of asset volatility provide a level of diversification in a portfolio unrelated to asset type. In the same manner which fixed income assets can provide diversification to equity assets due to the differences in the asset cash flows and price movements, volatility strategies can also provide effective diversification due to the difference in asset cash flows relative to price movements of the underlying assets. No level of diversification or non-correlation can ensure profits or guarantee against losses. Volatility as an Asset Class Any market is considered an asset class in itself if it can be traded independently. By definition, realized volatility cannot be traded. However, implied volatility, the market forecast of realized volatility, can traded as its own asset class. Trading VIX VIX is an index derived from market prices of a basket of options on S&P 500 Index. There is no direct way to trade VIX on a cash or spot basis. However, monthly futures on VIX trade on the CBOE Futures Exchange (CFE). There are several disadvantages of trading VIX futures. A primary disadvantage is that VIX is mean-reverting and does not have a long-term trend. An investor must therefore properly time the entries and exits to generate positive returns. A strategy solely based on timing cannot be expected to generate sustainable returns over the long run. A second disadvantage is that VIX futures expire every month, and need to be rolled into the next month upon expiry. This roll could cost as much as 10% every month. Therefore, trading VIX is not a sustainable strategy for the long-term. Trading Options on the S&P 500 Index An option price is a function of factors other than implied volatility including time to maturity, underlying price and strike. For any given strike and maturity, implied volatility and underlying price are the two variables that affect the option price. (Interest Rates also affect prices, but the effect is muted in the current low interest rate environment.)
Investing In Volatility 3 Vanilla Options One of the easiest means to trade volatility is to trade vanilla options. To be long volatility, one needs to purchase options. These trades are exposed to both volatility and market moves (changes in the price of the underlying asset). The effect of volatility cannot be isolated and therefore, such an investment would not exhibit the qualities of the volatility asset class discussed above. A long volatility trade involves buying call or put options. To negate the effect of the market moves, options need to be hedged against movements of the underlying asset ( delta hedging ). For small moves in the market, the portfolio stays stable. However, the option price is influenced by time decay. If an option is out of the money, the option price goes to zero as time passes. Time decay works in favor of the seller of options and against the buyer. A short volatility trade involves selling call or put options. To negate the effect of the market move, these options need to be delta hedged. For small moves in the market, the portfolio stays stable. Because the portfolio is still vulnerable to big moves in the market, plain vanilla options are not appropriate to trade the volatility asset class. Implied Volatility and Realized Volatility Implied volatilities tend to be higher than realized volatility in general. Some of the reasons for this include transaction costs and behavioral economics including the desire of equity fund managers to reduce portfolio volatility. In Figures 3 and 4, the spread between implied volatility and the following 30-day realized volatility is plotted. The spread is above 0 most of the time. Under distress conditions, the spread goes to below 0. The resulting characteristic is the majority of the time realized volatility tends to be lower than predicted by implied volatility. In cases where implied volatility predicts poorly, there tends to be a reversion to the mean: spread tends to jump higher. Figure 3: implied and realized volatilities VIX index (implied) REALIZED VOL Figure 4: implied and realized spread implied-realized
Investing In Volatility Volatility Swaps A volatility swap is a structured contract which pays off a pre-determined multiple of the difference between implied volatility and realized volatility at maturity. Therefore a volatility swap is a pure play on volatility. Timing does play an important role as can be seen in Figure 5. This graph is the value of a rolling variance swap futures published by the CFE. Figure 3: CBOE VOL-arb index VTY The line is steadily upward sloping until the distress events of 2008 drag it down. The drawdown was so deep that it has not recovered 4 years later. Actively Managed Options Portfolios After exploring a few different applications of trading volatility, each tactic has drawbacks that make an investment unsustainable for the long-term. An actively managed portfolio is a solution. Managing a portfolio of long and short options with a positive decay would ensure a steady upward sloping return curve. Dynamic portfolio management based on pre-emptive as well as reactive hedging mitigates some of the drawdowns during periods of a rapid rise of volatility in the markets. Portfolio risk management is the key to reducing a significant portion of the impact of a duress event on the impliedrealized spread. Moreover, the mean reversion property of volatility makes it possible to recover losses or drawdowns quickly if sound money management principles are employed. A successful short volatility portfolio must therefore incorporate dynamic rebalancing, risk management, and sound money management principles. Conclusion Volatility can be classified as an asset class in itself, since volatility behaves independently of the level of the underlying asset and can be traded in varied forms. An investment in the volatility asset class acts as a broad diversifier to traditional portfolios due to its low correlation to equities and fixed income. The short volatility asset class also offers the virtue of steady returns in most market conditions. After examining varied means to invest in the volatility asset class, it is evident that a balanced approach of net short volatility with long time decay can achieve sustainable and consistent returns in the long term. An actively managed portfolio of long and short options across different strikes and maturities with dynamic rebalancing harnesses the spread between implied and realized volatilities. As noted above, prudent risk management principles are vital to achieve these returns. Long: to purchase Short: to sell Standard Deviation: a mathematical calculation of variation from the average Correlation: a broad class of statistical relationships involving dependence
About the Author Anish Parvataneni, CFA is Portfolio Manager at LJM Partners, Ltd. Mr. Parvataneni has more than a decade of experience in the investment management industry. He began his career in 1995 managing a $200 mm domestic equity mutual fund at Unit Trust of India. In 2003 he served as a Financial Engineer at Citadel Investment Group in the Global Credit team. In this role, Anish assisted in the development and deployment of various risk systems and quantitative models. From 2006-2007 Anish assumed the role of a trader and managed a corporate bond options portfolio trading credit and interest rate derivatives. His responsibilities also included portfolio and risk management. Most recently, from 2008-2010, Anish worked as an algorithmic trader at Jump Trading in Chicago. In this role Anish was responsible for trading equity, interest rate and bond futures as well as other exchange traded products. Anish has a Master in Science in Computational Finance from Carnegie Melon University, a Master in Business Administration from Indian Institute of Management (IIM) in Lucknow, India and a Bachelor of Mechanical Engineering from the Regional Engineering College in Bhopal, India. Anish is also a Chartered Financial Analyst (CFA) charterholder. The material provided herein has been provided by LJM Partners, Ltd. and is for informational purposes only. LJM Partners, Ltd. serves as investment adviser to one or more mutual funds distributed through Northern Lights Distributors, LLC member FINRA. Northern Lights Distributors, LLC and LJM Partners, Ltd. are not affiliated entities.
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