Forecasting Volatility in the Financial Markets, Third Edition (Quantitative Finance)
Forecasting Volatility in the Financial Markets, Third Edition (Quantitative Finance)
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Manufacturer: Butterworth-Heinemann
Author: Stephen Satchell
Binding: Hardcover
Publication Date: 2007-04-06
Publisher: Butterworth-Heinemann
Label: Butterworth-Heinemann
Number Of Pages: 432 Features:
Editorial Review:
This new edition of 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 provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility.
Chapters new to this third edition: * What good is a volatility model? Engle and Patton * Applications for portfolio variety Dan diBartolomeo * A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish * Volatility modeling and forecasting in finance Xiao and Aydemir * An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey
* Leading thinkers present newest research on volatility forecasting *International authors cover a broad array of subjects related to volatility forecasting *Assumes basic knowledge of volatility, financial mathematics, and modelling Cached date: AWS Called=true You may also be interested in these products:
recent vintage 2007-12-23 For the seriously included financial modeller, who has a strong mathematical bent, the book is a good read. It explains several models used to try to characterise volatility. Typically, these go beyond the normal distribution; using, for example, the Generalised Error Distribution.
High order moments of the distributions are looked at. Like the consideration of what effects leptokurtosis have. Simulations also figure prominently in the book. So you can dry run your own models against some hopefully relevant "reality". In part, this is to look for simple forecasting rules that can then be applied in an actual market.
It should be no surprise that option pricing is extensively discussed. Starting with the partial differential method in Black-Scholes. There is a quick review of the considerable literature that has flowed from usage and refinement of Black-Scholes.
An attraction of the book is its recent vintage. Keeps you current on the best understanding of modelling.
