A Deeper Look at the Implied Volatility Spread as a Predictor of Stock Returns


Book Description

"I develop a new explanation of the implied volatility spread anomaly of Bali and Hovakimian (2009) and Cremers and Weinbaum (2010). The stock price observed in the stock market and the option implied stock price inferred from the option market are two noisy sources of information about the stock value. If these sources contain enough nonredundant information, the estimate of the stock value is between these prices, and the prices are expected to revert toward this estimate. This simple model is able to explain the reversals of the option implied prices toward the stock prices. Overall, the model of noisy prices is better aligned with the empirical patterns associated with the implied volatility spread phenomenon than other existing explanations of the phenomenon. I also document that if we invest in the implied volatility spread strategy at the end of each month, the next day excess return is 71 bps, which is almost twice as high as the average daily excess return of the implied volatility spread strategy. I show that this abnormal return from the end-of-month signal does not seem to be driven by seasonal trading patterns of institutional investors. If we take into account transaction costs, active trading on the implied volatility spread is too costly even for the marginal investor. This result is consistent with the model of noisy prices. However, the implied volatility spread can be used as a signal for the optimization of other trading strategies. If the implied volatility spread is used as a screening signal for a small stocks strategy, it modestly improves the performance of the baseline strategy"--Page vii.




Implied Volatility Spreads and Future Options Returns Around Information Events and Conditions


Book Description

While numerous prior studies report that call-put implied volatility spreads positively predict future stock returns, recent literature shows that the predictive relation is negative for future call option returns. We investigate whether and, if so, how the predictive relation for options returns is influenced by various information events and conditions. In addition to confirming an opposite predictive relation for both call and put returns, we show that the predictive relation is stronger during periods of earnings announcement and/or high sentiment. In addition, we find that investors learn from informed trading and revise their predictability bias by examining the impacts of information asymmetry, stock liquidity, and options liquidity on the predictive relationships.







Option-Implied Volatility Measures and Stock Return Predictability


Book Description

Using firm-level option and stock data, we examine the predictive ability of option-implied volatility measures proposed by previous studies and recommend the best measure using up-to-date data. Portfolio level analysis implies significant non-zero risk-adjusted returns on arbitrage portfolios formed on the call-put implied volatility spread, implied volatility skew, and realized-implied volatility spread. Firm-level cross-sectional regressions show that, the implied volatility skew has the most significant predictive power over various investment horizons. The predictive power persists before and after the 2008 Global Financial Crisis.




Trading Volatility


Book Description

This publication aims to fill the void between books providing an introduction to derivatives, and advanced books whose target audience are members of quantitative modelling community. In order to appeal to the widest audience, this publication tries to assume the least amount of prior knowledge. The content quickly moves onto more advanced subjects in order to concentrate on more practical and advanced topics. "A master piece to learn in a nutshell all the essentials about volatility with a practical and lively approach. A must read!" Carole Bernard, Equity Derivatives Specialist at Bloomberg "This book could be seen as the 'volatility bible'!" Markus-Alexander Flesch, Head of Sales & Marketing at Eurex "I highly recommend this book both for those new to the equity derivatives business, and for more advanced readers. The balance between theory and practice is struck At-The-Money" Paul Stephens, Head of Institutional Marketing at CBOE "One of the best resources out there for the volatility community" Paul Britton, CEO and Founder of Capstone Investment Advisors "Colin has managed to convey often complex derivative and volatility concepts with an admirable simplicity, a welcome change from the all-too-dense tomes one usually finds on the subject" Edmund Shing PhD, former Proprietary Trader at BNP Paribas "In a crowded space, Colin has supplied a useful and concise guide" Gary Delany, Director Europe at the Options Industry Council




Empirical Asset Pricing


Book Description

An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.




Implied Volatility Functions


Book Description

Abstract: Black and Scholes (1973) implied volatilities tend to be systematically related to the option's exercise price and time to expiration. Derman and Kani (1994), Dupire (1994), and Rubinstein (1994) attribute this behavior to the fact that the Black-Scholes constant volatility assumption is violated in practice. These authors hypothesize that the volatility of the underlying asset's return is a deterministic function of the asset price and time and develop the deterministic volatility function (DVF) option valuation model, which has the potential of fitting the observed cross-section of option prices exactly. Using a sample of S & P 500 index options during the period June 1988 through December 1993, we evaluate the economic significance of the implied deterministic volatility function by examining the predictive and hedging performance of the DV option valuation model. We find that its performance is worse than that of an ad hoc Black-Scholes model with variable implied volatilities.




Options Markets


Book Description

Includes the first published detailed description of option exchange operations, the first published treatment using only elementary mathematics and the first step-by-step procedure for implementing the Black-Scholes formula in actual trading.




Volatility Trading, + website


Book Description

In Volatility Trading, Sinclair offers you a quantitative model for measuring volatility in order to gain an edge in your everyday option trading endeavors. With an accessible, straightforward approach. He guides traders through the basics of option pricing, volatility measurement, hedging, money management, and trade evaluation. In addition, Sinclair explains the often-overlooked psychological aspects of trading, revealing both how behavioral psychology can create market conditions traders can take advantage of-and how it can lead them astray. Psychological biases, he asserts, are probably the drivers behind most sources of edge available to a volatility trader. Your goal, Sinclair explains, must be clearly defined and easily expressed-if you cannot explain it in one sentence, you probably aren't completely clear about what it is. The same applies to your statistical edge. If you do not know exactly what your edge is, you shouldn't trade. He shows how, in addition to the numerical evaluation of a potential trade, you should be able to identify and evaluate the reason why implied volatility is priced where it is, that is, why an edge exists. This means it is also necessary to be on top of recent news stories, sector trends, and behavioral psychology. Finally, Sinclair underscores why trades need to be sized correctly, which means that each trade is evaluated according to its projected return and risk in the overall context of your goals. As the author concludes, while we also need to pay attention to seemingly mundane things like having good execution software, a comfortable office, and getting enough sleep, it is knowledge that is the ultimate source of edge. So, all else being equal, the trader with the greater knowledge will be the more successful. This book, and its companion CD-ROM, will provide that knowledge. The CD-ROM includes spreadsheets designed to help you forecast volatility and evaluate trades together with simulation engines.




Competition for Listings


Book Description