Below I’ve collected links to some of my favorite white papers and presentations on volatility. I’ve organized them in the following categories:
- Volatility Concepts & Volatility Trading
- Probability Distributions—Normal and Otherwise
- The VIX and VIX Futures
- Volatility Contagion—Will Short Volatility Destroy the World?
- Variance Swaps—the Technology That Underlies VIX & VIX Futures
For an index of my 60+ posts on volatility see here.
Volatility Concepts & Volatility Trading
- “Volatility: A New Return Driver?” by Greggory Flinn & Roger Schreiner
- A good non-mathematical overview of volatility, volatility products including futures and a couple example trading strategies using volatility Exchange Traded Products
- Easy Volatility Investing by Tony Cooper
- Available via free download on the SSRN repository, this paper provides a good non-mathematical overview of volatility investing. It includes a good discussion on the Volatility Risk Premium (VRP) which is an important concept. It also provides detailed analysis of several volatility based trading schemes
- “Volatility Trading: Trading Volatility, Correlation, Term Structure and Skew” Bennett & Gil
- Over 200 pages of wide-ranging information—from covered calls to exotic options, to links between CDS spreads and implied volatility. Something for everyone.
Probability Distributions—Normal and Otherwise
- Tales of the Unexpected by Andrew Haldane
- This accessible paper (only one equation) is the best that I’ve ever read on the differences between processes accurately modeled by Gaussian/normal distributions and those better matched by power law distributions. I have seen this distinction made many times, but this paper provided examples and reasoning that really helped me internalize the differences. Most of our stock market computations (including Black & Scholes for option pricing) and risk management formulas assume normal (or log-normal) distributions but this paper lays out a compelling case for why power law distributions are often a better match.
- The normal distribution is the log-normal distribution by Werner Stahel & Eckhard Limpert
- This presentation does a very nice job of distinguishing between the normal and log-normal distribution and providing guidelines for when they should be used. Bottom line, for stock price distributions we should use the log-normal distribution.