Inside Volatility Filtering: Secrets of the Skew by Alireza Javaheri, the head of Equities Quantitative Research Americas at JP Morgan, is a book for quants. The first edition, which appeared ten years ago, was based on his Ph.D. dissertation and won the Wilmott Award. In this revised, updated second edition (Wiley, 2015), Javaheri draws on feedback he received at conferences and in the courses he taught at NYU’s Courant Institute of Mathematical Sciences and at Baruch College.
My mathematical skills, though ever improving, are not yet up to the task of writing a meaningful review of this book. So consider this a notice rather than a review.
Here’s a description of the book’s contents from the jacket copy: “Inside Volatility Filtering, Second Edition presents a new approach to volatility estimation identifying financial econometrics based on a more accurate estimation of the hidden state. Based on the idea of ‘filtering,’ this practical guide lays out a two-step framework involving a Chapman-Kolmogorov prior distribution followed by Bayesian posterior distribution to develop a robust estimation based on all available information. This new edition gives you an edge by showing you how to: base volatility estimations on more accurate data, integrate past observation with Bayesian probability, exploit posterior distribution of the hidden state for optimal estimation, and boost trade profitability by identifying ‘skewness’ opportunities.”