This paper reviews various methods for extracting statistical information implicit in market prices of options. We present several methods for state price densities from options paneldata: lognormal Edgeworth expansions, cumulant expansions, Hermite polynomial expansions, non-parametric estimators, and maximum entropy methods. Parametric methods such as implied binomial trees and mixtures of lognormals are also briefly discussed.We discuss the advantages and drawbacks of each method, the interpretation of their results in economic terms, their theoretical consequences and their relevance for applications.The present text is an augmented version of a lecture presented at Eotvos University, Budapest in July 1997. The style is introductory and self contained.

Even the best Wall Street investors make mistakes. No matter how savvy or experienced, all financial practitioners eventually let bias, overconfidence, and emotion cloud their judgement and misguide their actions. Yet most financial decision-making models fail to factor in these fundamentals of human nature. In Beyond Greed and Fear, the most authoritative guide to what really influences the decision-making process, Hersh Shefrin uses the latest psychological research to help us understand the human behavior that guides stock selection, financial services, and corporate financial strategy. Shefrin argues that financial practitioners must acknowledge and understand behavioral finance--the application of psychology to financial behavior--in order to avoid many of the investment pitfalls caused by human error. Through colorful, often humorous real-world examples, Shefrin points out the common but costly mistakes that money managers, security analysts, financial planners, investment bankers, and corporate leaders make, so that readers gain valuable insights into their own financial decisions and those of their employees, asset managers, and advisors. According to Shefrin, the financial community ignores the psychology of investing at its own peril. Beyond Greed and Fear illuminates behavioral finance for today's investor. It will help practitioners to recognize--and avoid--bias and errors in their decisions, and to modify and improve their overall investment strategies.

An unprecedented book on option pricing! For the first time, the basics on modern option pricing are explained ``from scratch'' using only minimal mathematics. Market practitioners and students alike will learn how and why the Black-Scholes equation works, and what other new methods have been developed that build on the success of Black-Shcoles. The Cox-Ross-Rubinstein binomial trees are discussed, as well as two recent theories of option pricing: the Derman-Kani theory on implied volatility trees and Mark Rubinstein's implied binomial trees. Black-Scholes and Beyond will not only help the reader gain a solid understanding of the Balck-Scholes formula, but will also bring the reader up to date by detailing current theoretical developments from Wall Street. Furthermore, the author expands upon existing research and adds his own new approaches to modern option pricing theory. Among the topics covered in Black-Scholes and Beyond: detailed discussions of pricing and hedging options; volatility smiles and how to price options ``in the presence of the smile''; complete explanation on pricing barrier options.

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.

A new research design is introduced for the empirical analysis of the relationship between implied volatility and ex-post realized volatility. The dynamics of volatility are emphasized, and the analysis is cast in terms of non-overlapping data, so that exactly one implied and one realized volatility estimate pertain to each period under consideration. The conclusions from the empirical analysis when using our design are significantly different from those previously reached. Recent literature indicates that implied volatility contains little information about future volatility, beyond that contained in the history of realized volatility. We show that on the contrary, implied volatility efficiently predicts future realized volatility and in particular subsumes the information content of past realized volatility.