Forecasting Volatility in the Financial Markets, Third Edition

Stephen Satchell,John Knight

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.

Contents:

1 Volatility modelling and forecasting in finance
2 What good is a volatility model?
3 Applications of portfolio variety
4 A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices
5 An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility
6 Stochastic volatility and option pricing
7 Modelling slippage: an application to the bund futures contract
8 Real trading volume and price action in the foreign exchange markets
9 Implied risk-neutral probability density functions from option prices: a central bank perspective
10 Hashing GARCH: a reassessment of volatility forecasting performance
11 Implied volatility forecasting: a comparison of different procedures including fractionally integrated models with applications to UK equity options
12 GARCH predictions and the predictions of option prices
13 Volatility forecasting in a tick data model
14 An econometric model of downside risk
15 Variations in the mean and volatility of stock returns around turning points of the business cycle
16 Long memory in stochastic volatility
17 GARCH processes – some exact results, some difficulties and a suggested remedy
18 Generating composite volatility forecasts with random factor betas