'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

Contributors; Introduction; Volatility modelling in finance; Stochastic volatility and option pricing; Modelling slippage: an application to the bund futures contract; Real trading volume and price action in the foreign exchange markets; Implied risk-neutral probability density functions from option prices: a central bank perspective; Hashing GARCH: a reassessment of volatility forecasting performance; Implied volatility forecasting: a comparison of different procedures including fractionally integrated models with applications to UK equity options; GARCH predictions and the predictions of option prices; Volatility forecasting in a tick data model; An econometric model of downside risk; Variations in the mean and volatility of stock returns around turning points of the business cycle; Long memory in stochastic volatility; GARCH processes - some exact results, some difficulties and a suggested remedy; Generating composite volatility forecasts with random factor betas; The information content of the FTSE 100 Index Option implied volatility and its structural changes with links to loss aversion; Index.