A Practical Guide to Forecasting Financial Market Volatility
Published on 19. April 2005
Book
Hardback
236 pages
978-0-470-85613-0 (ISBN)
Description
Volatility forecasting is crucial for option pricing, risk management and portfolio management. This book gives clear and practical guidance on how to model and forecast volatility using only volatility models that have been tested for their forecasting performance. The book focuses on describing, evaluating and comparing research in volatility forecasting and provides some background on volatility definition, estimation and some principles on forecasts evaluation. The book covers both time series econometric volatility models and implied volatility model based on Black-Scholes and continuous time stochastic volatility option pricing models.
"The present book by Professor Ser-Huang Poon surveys this literature carefully and provides a very useful summary of the results available. By so doing, she allows any interested worker to quickly catch up with the field and also to discover the areas that are still available for further exploration."
--Sir Clive W. J. Granger, University of California in San Diego
"Professor Poon exposes in her book current state-of-the-art volatility forecasting methods. Beginning with a description of various conditional volatility models, be it discrete or continuous, the link with option pricing models is well established. The book proceeds with surveying the current volatility literature: what type of volatility should be used to price options, how can volatility of various assets be predicted, how volatility can be used within a value-at-risk setting. This well written book should be useful both for the practitioner and the academic/student interested in volatility."
--Professor Michael Rockinger, FAME and University of Lausanne, Switzerland
More details
Product info
gebunden
Series
Edition
1. Auflage
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
With dust jacket
Dimensions
Height: 235 mm
Width: 157 mm
Thickness: 19 mm
Weight
556 gr
ISBN-13
978-0-470-85613-0 (9780470856130)
Schweitzer Classification
Other editions
Additional editions
Ser-Huang Poon
A Practical Guide to Forecasting Financial Market Volatility
E-Book
08/2005
Wiley
€80.99
Available for download
Person
Dr SER-HUANG POON was promoted to Professor of Finance at Manchester University in 2003. Prior to that, she was a senior lecturer at Strathclyde University. Ser-Huang graduated from the National University of Singapore and obtained her masters and PhD from Lancaster University, UK. She has researched financial market volatility for many years and has published in many top ranking peer reviewed finance and financial econometric journals with many co-authors from around the world. Her financial market volatility work was cited as a reference reading on the Nobel web site in 2003.
Content
Foreword by Clive Granger.
Preface.
1 Volatility Definition and Estimation.
1.1 What is volatility?
1.2 Financial market stylized facts.
1.3 Volatility estimation.
1.4 The treatment of large numbers.
2 Volatility Forecast Evaluation.
2.1 The form of Xt.
2.2 Error statistics and the form of µt.
2.3 Comparing forecast errors of different models.
2.4 Regression-based forecast efficiency and orthogonality test.
2.5 Other issues in forecast evaluation.
3 Historical Volatility Models.
3.1 Modelling issues.
3.2 Types of historical volatility models.
3.3 Forecasting performance.
4 Arch.
4.1 Engle (1982).
4.2 Generalized ARCH.
4.3 Integrated GARCH.
4.4 Exponential GARCH.
4.5 Other forms of nonlinearity.
4.6 Forecasting performance.
5 Linear and Nonlinear Long Memory Models.
5.1 What is long memory in volatility?
5.2 Evidence and impact of volatility long memory.
5.3 Fractionally integrated model.
5.4 Competing models for volatility long memory.
6 Stochastic Volatility.
6.1 The volatility innovation.
6.2 The MCMC approach.
6.3 Forecasting performance.
7 Multivariate Volatility Models.
7.1 Asymmetric dynamic covariance model.
7.2 A bivariate example.
7.3 Applications.
8 Black-Scholes.
8.1 The Black-Scholes formula.
8.2 Black-Scholes and no-arbitrage pricing.
8.3 Binomial method.
8.4 Testing option pricing model in practice.
8.5 Dividend and early exercise premium.
8.6 Measurement errors and bias.
8.7 Appendix: Implementing Barone-Adesi and Whaley's efficient algorithm.
9 Option Pricing with Stochastic Volatility.
9.1 The Heston stochastic volatility option pricing model.
9.2 Heston price and Black-Scholes implied.
9.3 Model assessment.
9.4 Volatility forecast using the Heston model.
9.5 Appendix: The market price of volatility risk.
10 Option Forecasting Power.
10.1 Using option implied standard deviation to forecast volatility.
10.2 At-the-money or weighted implied?
10.3 Implied biasedness.
10.4 Volatility risk premium.
11 Volatility Forecasting Records.
11.1 Which volatility forecasting model?
11.2 Getting the right conditional variance and forecast with the 'wrong' models.
11.3 Predictability across different assets.
12 Volatility Models in Risk Management.
12.1 Basel Committee and Basel Accords I & II.
12.2 VaR and backtest.
12.3 Extreme value theory and VaR estimation.
12.4 Evaluation of VaR models.
13 VIX and Recent Changes in VIX.
13.1 New definition for VIX.
13.2 What is the VXO?
13.3 Reason for the change.
14 Where Next?
Appendix.
References.
Index.