Building on the widely-used double-lognormal approach by Bahra (1997), this paper presents a multi-lognormal approach with restrictions to extract risk-neutral probability density functions (RNPs) for various asset classes. The contributions are twofold: first, on the technical side, the paper proposes useful transformation/restrictions to Bahra’s original formulation for achieving economically sensible outcomes. In addition, the paper compares the statistical properties of the estimated RNPs among major asset classes, including commodities, the S&P 500, the dollar/euro exchange rate, and the US 10-year Treasury Note. Finally, a Monte Carlo study suggests that the multi-lognormal approach outperforms the double-lognormal approach.

This volume is a collection of classical and recent empirical studies of currency options and their implications for issues of exchange rate economics, such as exchange rate risk premium, volatility, market expectations, and credibility of exchange rate regimes. It contains applications on how to extract useful information from option market data for financial forecasting policy purposes. The subjects are discussed in a self-contained, user-friendly format, with introductory chapters on currency option theory and currency option markets.The book can be used as supplementary reading for graduate finance and international economics courses, as training material for central bank and regulatory authorities, or as a reference book for financial analysts.

This book is a slightly revised version of my doctoral dissertation which has been accepted by the Department of Economics and Business Administration of the Justus-Liebig-Universitat Giessen in July 2002. I am indebted to my advisor Prof. Dr. Volbert Alexander for encouraging and supporting my research. I am also grateful to the second member of the doctoral committee, Prof. Dr. Horst Rinne. Special thanks go to Dr. Ralf Ahrens for providing part of the data and to my colleague Carsten Lang, who spent much time reading the complete first draft. Wetzlar, January 2003 Martin Mandler Contents 1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Part I Theoretical Foundations 2 Arbitrage Pricing and Risk-Neutral Probabilities........ .. 7 2.1 Arbitrage Pricing in the Black/Scholes-Merton Model... . . .. . 7 2.2 The Equivalent Martingale Measure and Risk-Neutral Valuation ............................................... 11 2.3 Extracting Risk-Neutral Probabilities from Option Prices. . . .. 13 2.4 Summary............................................... 15 Appendix 2A: The Valuation Function in the Black/Scholes-Merton Model .................................................. 16 Appendix 2B: Some Further Details on the Replication Strategy ... 21 3 Survey of the Related Literature .......................... 23 3.1 The Information Content of Forward and Futures Prices. . . .. . 24 3.2 The Information Content of Implied Volatilities ............. 25 3.2.1 Implied Volatilities and the Risk-Neutral Probability Density .......................................... 27 3.2.2 The Term Structure of Implied Volatilities. . . . . . . .. . . 29 . 3.2.3 The Forecasting Information in Implied Volatilities. . .. 30 3.2.4 Implied Correlations as Forecasts of Future Correlations 43 VIII Contents 3.3 The Skewness Premium ..... . . . . . . . . . . . . . . . . . . .. . . 45 . . . . . . .

This book shows how current and recent market prices convey information about the probability distributions that govern future prices. Moving beyond purely theoretical models, Stephen Taylor applies methods supported by empirical research of equity and foreign exchange markets to show how daily and more frequent asset prices, and the prices of option contracts, can be used to construct and assess predictions about future prices, their volatility, and their probability distributions. Stephen Taylor provides a comprehensive introduction to the dynamic behavior of asset prices, relying on finance theory and statistical evidence. He uses stochastic processes to define mathematical models for price dynamics, but with less mathematics than in alternative texts. The key topics covered include random walk tests, trading rules, ARCH models, stochastic volatility models, high-frequency datasets, and the information that option prices imply about volatility and distributions. Asset Price Dynamics, Volatility, and Prediction is ideal for students of economics, finance, and mathematics who are studying financial econometrics, and will enable researchers to identify and apply appropriate models and methods. It will likewise be a valuable resource for quantitative analysts, fund managers, risk managers, and investors who seek realistic expectations about future asset prices and the risks to which they are exposed.

'Forecasting Volatility in the Financial Markets' assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting edge modelling and forecasting techniques. It then uses a technical survey to explain the different ways to measure risk and define the different models of volatility and return.The editors have brought together a set of contributors that give the reader a firm grounding in relevant theory and research and an insight into the cutting edge techniques applied in this field of the financial markets.This book is of particular relevance to anyone who wants to understand dynamic areas of the financial markets.* Traders will profit by learning to arbitrage opportunities and modify their strategies to account for volatility.* Investment managers will be able to enhance their asset allocation strategies with an improved understanding of likely risks and returns.* Risk managers will understand how to improve their measurement systems and forecasts, enhancing their risk management models and controls.* Derivative specialists will gain an in-depth understanding of volatility that they can use to improve their pricing models.* Students and academics will find the collection of papers an invaluable overview of this field.This book is of particular relevance to those wanting to understand the dynamic areas of volatility modeling and forecasting of the financial marketsProvides the latest research and techniques for Traders, Investment Managers, Risk Managers and Derivative Specialists wishing to manage their downside risk exposure Current research on the key forecasting methods to use in risk management, including two new chapters

This book provides a manual on quantitative financial analysis. Focusing on advanced methods for modelling financial markets in the context of practical financial applications, it will cover data, software and techniques that will enable the reader to implement and interpret quantitative methodologies, specifically for trading and investment. Includes contributions from an international team of academics and quantitative asset managers from Morgan Stanley, Barclays Global Investors, ABN AMRO and Credit Suisse First Boston. Fills the gap for a book on applied quantitative investment & trading models Provides details of how to combine various models to manage and trade a portfolio