Forecasting Volatility
in the Financial Markets

For researchers or financial engineers, Knight and Satchell offer an edited collection of 15 articles on financial econometrics.

 

The first quarter of the book comprises two wonderful survey articles. The first of these covers the recent literature on conditionally heteroskedastic time series models, especially

GARCH models,

regime-switching models, and

threshold models.

Its focus is on univariate models, but multivariate models are also discussed.

The second survey article covers the recent literature on option pricing models that incorporate conditional heteroskedasticity.

Both survey articles are sophisticated and very well written. They offer a treasure trove of references. Be aware that they are technical. They assume a fair amount of prior knowledge about time series modeling. If you are comfortable reading Hamilton (1994), you should be fine reading them.

The remainder of the book comprises 13 articles on various topics. About half relate to volatility forecasting. The rest cover other topics.

There are two nice articles assessing intra-day patterns of volatility and trading volume in futures and FX markets. They also explore slippage (impact costs) associated with large trades.

Contents

1. Volatility modeling in finance

2. Stochastic volatility and option pricing

3. Modelling slippage: an application to the bund futures contract

4. Real trading volume and price action in the foreign exchange markets

5. Implied risk-neutral probability density functions from option prices: a central bank perspective

6. Hashing GARCH: a reassessment of volatility forecasting performance

7. Implied volatility forecasting: a comparison of different procedures including fractionally integrated models with applications to UK equity options

8. GARCH predictions and the predictions of option prices

9. Volatility forecasting in a tick data model

10. An econometric model of downside risk

11. Variations in the mean and volatility of stock returns around turning points of the business cycle

12. Long memory in stochastic volatility

13. GARCH processes - some exact results, some difficulties and a suggested remedy

14. Generating composite volatility forecasts with random factor betas

15. The information content of the FTSE100 index option implied volatility and its structural changes with links to loss aversion

There are several articles on GARCH processes. Another explores using a fractionally integrated ARMA model as an alternative to IGARCH for modeling long-memory volatility. Still another applies asymmetric ARCH models to modeling downside risk.

Most of these articles are not too technical. Readers are likely to flip through them, reading those that they find interesting, and skipping the rest.

In summary, the reason to buy this book is the two outstanding survey articles at the beginning of the book. The remaining articles are interesting, and I am sure most readers will find several useful in their own work. Reading through them is a bit like reading a lengthy issue of a financial econometrics journal—some articles will interest you; others will not.

Who is this book for? I highly recommend it for researchers and financial engineers.

  

 

 

Ads by Contingency Analysis.

Advertise on this site.
 

disclaimer

website: http://www.contingencyanalysis.com
books direct link: http://www.riskbook.com
copyright © Contingency Analysis, 1996 - current