Description 
viii, 415 pages : illustrations ; 25 cm 
Series 
Quantitative finance series 

Quantitative finance series.

Contents 
Machine derived contents note: List of contributors vii  Preface to third edition ix  Introduction xi  1 Volatility modelling and forecasting in finance 1  Linlan Xiao and Abdurrahman Aydemir  2 What good is a volatility model? 47  Robert F. Engle and Andrew J. Patton  3 Applications of portfolio variety 65  Dan diBartolomeo  4 A comparison of the properties of realized variance for the FTSE 100  and FTSE 250 equity indices 73  Rob Cornish  5 An investigation of the relative performance of GARCH models versus  simple rules in forecasting volatility 101  Thomas A. Silvey  6 Stochastic volatility and option pricing 131  George J. Jiang  7 Modelling slippage: an application to the bund futures contract 173  Emmanuel Acar and Edouard Petitdidier  8 Real trading volume and price action in the foreign exchange markets 187  Pierre Lequeux  9 Implied riskneutral probability density functions from option prices:  a central bank perspective 201  Bhupinder Bahra  10 Hashing GARCH: a reassessment of volatility forecasting performance 227  George A. Christodoulakis and Stephen E. Satchell  11 Implied volatility forecasting: a comparison of different procedures  including fractionally integrated models with applications to UK  equity options 249  Soosung Hwang and Stephen E. Satchell  12 GARCH predictions and the predictions of option prices 279  John Knight and Stephen E. Satchel!  13 Volatility forecasting in a tick data model 295  L.C.G. Rogers  14 An econometric model of downside risk 301  Shaun Bond  15 Variations in the mean and volatility of stock returns around  turning points of the business cycle 333  Gabriel PerezQuiros and Allan Timmermann  16 Long memory in stochastic volatility 351  Andrew C. Harvey  17 GARCH processes  some exact results, some difficulties  and a suggested remedy 365  John L. Knight and Stephen E. Satchell  18 Generating composite volatility forecasts with random factor betas 391  George A. Christodoulakis 
Summary 
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 cuttingedge 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 uptodate 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 
Bibliography 
Includes bibliographical references and index 
Notes 
Print version record 
Subject 
Options (Finance)  Mathematical models.


Securities  Prices  Mathematical models.


Stock price forecasting  Mathematical models.

Author 
Knight, John L.


Satchell, S. (Stephen)

LC no. 
2007278282 
ISBN 
075066942X 

9780750669429 
