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, 198
Multifractal Volatility..Theory, Forecasting, and Pricing
โ Scribed by Laurent E. Calvet, Adlai J. Fisher
- Publisher
- Academic Press
- Year
- 2008
- Tongue
- English
- Leaves
- 252
- Series
- Academic Press Advanced Finance
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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. รยท Presents a powerful new technique for forecasting volatility รยท Leads the reader intuitively from existing volatility techniques to the frontier of research in this field by top scholars at major universities. รยท The first comprehensive book on multifractal techniques in finance, a cutting-edge field of research
โฆ Table of Contents
cover.jpg......Page 1
sdarticle.pdf......Page 2
sdarticle_001.pdf......Page 4
sdarticle_002.pdf......Page 7
sdarticle_003.pdf......Page 8
sdarticle_004.pdf......Page 18
sdarticle_005.pdf......Page 23
sdarticle_006.pdf......Page 52
sdarticle_007.pdf......Page 82
sdarticle_008.pdf......Page 95
sdarticle_009.pdf......Page 104
sdarticle_010.pdf......Page 120
sdarticle_011.pdf......Page 141
sdarticle_012.pdf......Page 173
sdarticle_013.pdf......Page 188
sdarticle_014.pdf......Page 192
sdarticle_015.pdf......Page 223
sdarticle_016.pdf......Page 245
๐ SIMILAR VOLUMES
<p>This book demonstrates the power of neural networks in learning complex behavior from the underlying financial time series data. The results presented also show how neural networks can successfully be applied to volatility modeling, option pricing, and value-at-risk modeling. These features mean
Although multifractals are rooted in probability, much of the related literature comes from the physics and mathematics arena. Multifractals: Theory and Applications pulls together ideas from both these areas using a language that makes them accessible and useful to statistical scientists. It provid
Although multifractals are rooted in probability, much of the related literature comes from the physics and mathematics arena. Multifractals: Theory and Applications pulls together ideas from both these areas using a language that makes them accessible and useful to statistical scientists. It provid
Although multifractals are rooted in probability, much of the related literature comes from the physics and mathematics arena. Multifractals: Theory and Applications pulls together ideas from the both areas using a language that makes them accessible and useful to statistical scientists. It provides