Mon, Nov 3, 2008 | Jared Woodard
Volatility as an Asset Class: A guide to buying, selling, and trading third-generation volatility products, ed. Israel Nelken (London: Risk Books, 2007). Israel Nelken, one of the members of the CBOE New Products Committee, has collected 11 essays on the theory and practice of trading volatility as a distinct asset class. The first half of the book examines the measurement of volatility and ways to employ volatility models on several traditional underlying products. The second half is devoted to discussion of new volatility products, including the VIX and variance swaps. For brevity’s sake, we will mention the topic of each essay but focus our comments on the chapters of most interest to our readers. This is a text written for institutional practitioners and academics, and is not appropriate for casual retail traders; at the very least, readers should have some stochastic calculus and detailed knowledge of options.
Nelken’s introduction includes a couple-paragraph history of the VIX: an academic paper by Neuberger in (Nelken 1995) was the post-LTCM inspiration for (Derman 1999) and subsequently for the formula that Derman et al. at the CBOE used to construct the VIX. Chapter 1 examines processes for building volatility surfaces. Chapter 2 examines volatility, and especially its observed risk premium, as analogous to fixed income assets. Chapter 3 tests the claim that trend following futures funds are functionally long volatility. Chapter 4 examines basket volatility and the correlation among several world indices. Chapter 5 is a narrative interlude on the advantages of appreciating the inefficiency of markets. Chapter 6 compares several models for measuring implied volatility, including Black-Scholes, VIX, “Model-Free” IV, and several Corridor IV models. Chapter 7 introduces second-generation volatility products, including variance swaps, gamma swaps, and corridor and conditional variance swaps. Chapter 8 examines exchange-traded volatility products, specifically VIX futures, VIX options, and variance futures. Chapter 9 offers a volatility-triggered trading strategy on the KOSPI200 index. Chapter 10 publishes formulas for pricing and hedging variance swaps. Chapter 11 considers the advantages of corridor variance swaps.
Volatility and Mean Reversion
Kim’s analysis of volatility in the Korean KOSPI200 options leads him to suggest a strategy based on the mean-reverting nature of volatility which, as it turns out, is remarkably similar to the strategy we published last month in Trading Volatility at the Extremes. The idea is that when a volatility index is 2 standard deviations above or below a short-term moving average (30-day in Kim’s example), mean-reversion should correlate with an inverse movement in the underlying index. This essay only examines results for 2007, so our study (such as it is) actually seems more robust.
The Volatility Risk Premium
One of the more persistent themes across the book was the existence of a quantifiable and persistent volatility risk premium. That such a premium exists is wholly intuitive – sellers will demand to be compensated for being short volatility – but the more interesting detail is that historically, the risk premium baked into implied volatility appears to be consistently higher than what realized volatility would warrant. (That little nuance is actually the core thesis of our iron condor newsletter strategy.) The first three chapters discuss some methods for exploiting this implied-realized differential, including delta-hedging option selling, trading VIX futures, and trading variance swaps.
Corridor Variance Swaps
A corridor variance swap is a swap that includes the realized squared return of the underlying in the floating part of the payout only if the underlying is within a predetermined corridor or range. The advantage of this type of product from a trader’s point of view is that it allows him to express a directional view on volatility that is contingent on price, or to hedge a short volatility position. Several authors devoted considerable space to incorporating corridor-based models into their analysis of volatility; the authors of one paper even concluded that “the narrow corridor or BSIV [Black-Scholes] measures are more useful predictors of future volatility than the broad corridor MFIV ["model-free" implied volatility] or VIX measures” (p. 145) because the broader models embed larger and more time-sensitive risk premia. Why should ordinary humans care about corridor swaps and their possible relative forecasting advantages? Because the decision about how wide or narrow a range of data to consider when forecasting volatility is one that traders make every day. One of the biggest changes that took place in the 2003 move from the “old VIX” (now VXO) to the new/current VIX was the inclusion of out-of-the-money options rather than only at- and near-the-money options. If, as several authors here suggest, OTM option prices tend to include larger risk premia, then the possibility exists that an ATM/NTM-only VIX (using the VXO methodology but on SPX rather than OEX options) could provide better volatility forecasting. In other words, a VIX calculated from corridor variance swaps instead of ordinary variance swaps (from which the current index is derived) might offer some comparative advantage. Photo courtesy of Flickr user lavaland.