Forecasting Volatility in the Financial MarketsBy
- Stephen Satchell, Consultant to financial institutions and Reader in Financial Econometrics at Trinity College, Cambridge, Stephen Satchell is Editor-in-Chief of the Journal of Asset Management and Derivatives, Use, Trading, and Regulation. He has edited or authored over 20 books on finance.
- John Knight, FCIBSE (Haden Young Ltd), UK
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
Primary audience: Investment Professionals and academics
Hardbound, 432 Pages
Imprint: Butterworth Heinemann
- 1 Volatility modeling and forecasting in finance, by L. Xiao and A. Aydemir;2 What good is a volatility model?, by R.F.Engle and A. J. Patton; 3 Applications of portfolio Variety, by D. diBartolomeo; 4 A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices, by R. Cornish;5 An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility, by T. A. Silvey;6 Stochastic volatility and option pricing, by G. J. Jiang; 7 Modelling slippage: an application to the bund futures contract, by E.Acar and E. Petitdidier; 8 Real trading volume and price action in the foreign exchange markets, by P. Lequeux; 9 Implied risk-neutral probability density functions from option prices: a central bank perspective, by B. Bahra; 10 Hashing GARCH: a reassessment of volatility forecasting performance, by G. A. Christodoulakis and S. E. Satchell; 11 Implied volatility forecasting: a comparison of different procedures including fractionally integrated models with applications to UK equity options, by S. Hwang and S. E. Satchell; 12 GARCH predictions and the predictions of option prices, by J. Knight and S. E. Satchell 13 Volatility forecasting in a tick data model, by L. C. G. Rogers; 14 An econometric model of downside risk, by S. Bond; 15 Variations in the mean and volatility of stock returns around turning points of the business cycle, by G. Perez-Quiros and A. Timmermann; 16 Long memory in stochastic volatility, by A. C. Harvey; 17 GARCH processes some exact results, some difficulties and a suggested remedy, by J. L. Knight and S. E. Satchell; 18 Generating composite volatility forecasts with random factor betas, by G. A. Christodolakis