"Best New Quantitative Finance Book of the Year" (Wilmott Awards 2006)
From the Inside Flap
With Inside Volatility Arbitrage: The Secrets of Skewness, Alireza Javaheri provides one of the most comprehensive looks at this important topic. Divided into three informative sections, this guide focuses on developing methodologies for estimating stochastic volatility (SV) parameters from the stock-price time-series under a classical framework.
In Section 1: The Volatility Problem, Javaheri introduces the concept of various parametric SV models and examines literature on the subject of non-deterministic volatility. Here, you'll receive in-depth information on the relationship between volatility and the stock and derivatives markets, detailed insights on Brownian motion for stock price returns, and option pricing techniques such as inversion of the Fourier transform and mixing Monte Carlo. You'll also gain invaluable knowledge on a variety of models, from local volatility and stochastic volatility models to pure-jump models.
In Section 2: The Inference Problem, Javaheri tackles the notion of inference (or parameter estimation) for parametric SV modelsbriefly analyzing cross-sectional inference and then focusing on time-series inference. Here you'll discover how to estimate model parameters using two possible sets of data: options prices and historic stock prices.
Finally, in Section 3: The Consistency Problem, Javaheri shows you how to apply parametric inference methodologies to a few assets. He also reveals why you should question the consistency of information contained in the options markets and the stock market.
Filled with in-depth insights, proven models, and illustrative charts, Inside Volatility Arbitrage will help you realize when "skewness" may present valuable trading opportunities, as well as why it can be so profitable.