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| MULTIFRACTAL VOLATILITY
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Theory, Forecasting, and Pricing
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By
Laurent Calvet, Professor, Chair in Finance - Tanaka Business School, Imperial College London, UK
Adlai Fisher, Faculty of Commerce, University of British Columbia, Vancouver, Canada
Included in series
Academic Press Advanced Finance ,
Description
Calvet and Fisher present a powerful, new technique for volatility forecasting that draws on insights from the use of multifractals in
the natural sciences and mathematics and provides a unified treatment of the use of multifractal techniques in finance. A large existing
literature (e.g., Engle, 1982; Rossi, 1995) models volatility as an average of past shocks, possibly with a noise component. This approach
often has difficulty capturing sharp discontinuities and large changes in financial volatility. Their research has shown the advantages
of modelling volatility as subject to abrupt regime changes of heterogeneous durations. Using the intuition that some economic phenomena
are long-lasting while others are more transient, they permit regimes to have varying degrees of persistence. By drawing on insights
from the use of multifractals in the natural sciences and mathematics, they show how to construct high-dimensional regime-switching models
that are easy to estimate, and substantially outperform some of the best traditional forecasting models such as GARCH. The goal of their
book is to popularize the approach by presenting these exciting new developments to a wider audience. They emphasize both theoretical
and empirical applications, beginning with a style that is easily accessible and intuitive in early chapters, and extending to the most
rigorous continuous-time and equilibrium pricing formulations in final chapters.
Audience
Finance practitioners, academics, and students, and econometriciansSecondary readership: Mathematicians, statisticians, and natural scientists interested in fractals
Contents
Contents
Preface
Chapter 1 Introduction
Chapter 2 Background
2.1 Autoregressive Volatility Modeling
2.2 Multifractals
in the Natural Sciences
Chapter 3 The Multifractal Volatility Model: The MMAR
3.1 The Multifractal Model of Asset Returns
3.2 An Extension
with Autocorrelated Returns
3.3 Empirical Evidence
3.4 Discussion
Chapter 4 The Marko-Switching Multifractal (MSM) in Discrete Time
4.1
MSM Construction in Discrete Time
4.2 Maximum Likelihood Estimation
4.3 Empirical Results
4.4 Comparison with Alternative Models
4.5
Discussion
Chapter 5. Multivariate MSM
5.1 Comovement of Univariate Volatility Components
5.2 A Bivariate Multifrequency Model
5.3 Inference
5.4 Empirical Results
5.5 Extension to Many Assets
5.6 Discussion
Chapter 6 The Marko-Switching Multifractal in Continuous Time
6.1
MSM in Continuous - Time
6.2 The Financial Model
6.3 Forecasting the Distribution of Returns
6.4 Discussion
Chapter 7 Multifrequency
News and Stock Returns
7.1 An asset pricing model with regime-switching dividents
7.2 Volatility feedback with multifrequency shocks
7.3 Empirical results with fully informaed investros
7.4 Learning about volatility and endogenous skewness
7.5 Robustness checks, preference
implications, and extension
7.6 Discussion
Chapter 8 Multifrequency Jump Diffusions
8.1 An Equilibrium Model with Endogenous Price Jumps
8.2 A Multifrequency Jump-Difussion for Equilibrium Stock Prices
8.3 Price Dynamics with an Infinity of Frequencies
8.4 Recursive Utility
and Priced Jumps
8.5 Discussion
Chapter 9 ConclusionAppendices
| Bibliographic details |
Hardbound, 272 pages, publication date: SEP-2008
ISBN-13: 978-0-12-150013-9
ISBN-10: 0-12-150013-6
Imprint: ACADEMIC PRESS
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| Price and Ordering |
Price:
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USD 75.95
GBP 45.99
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Last update: 5 Sep 2009
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