Ser-Huang Poon

A Practical Guide to Forecasting Financial Market Volatility

• Gebundenes Buch

Produktbeschreibung

Financial market volatility forecasting is one of today's most important areas of expertise forprofessionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modeling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. Forecasting Volatility in Financial Markets provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.

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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

Produktdetails

• Verlag: Wiley & Sons
• Artikelnr. des Verlages: 14585613000
• 1. Auflage
• Seitenzahl: 200
• Erscheinungstermin: 27. Mai 2005
• Englisch
• Abmessung: 235mm x 157mm x 19mm
• Gewicht: 500g
• ISBN-13: 9780470856130
• ISBN-10: 0470856130
• Artikelnr.: 14042838

Autorenporträt

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.

Inhaltsangabe

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.