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Multifractal volatility theory, forecasting, and pricing by Laurent E. Calvet

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Published by Academic Press in Burlington, MA, London .
Written in English

Subjects:

  • Finance -- Econometric models,
  • Economic forecasting -- Econometric models,
  • Multifractals

Book details:

Edition Notes

Includes bibliographical references (p. [229]-250) and index.

Statementby Laurent E. Calvet, Adlai J. Fisher.
SeriesAcademic Press advanced finance series
ContributionsFisher, Adlai.
Classifications
LC ClassificationsHB141 .C35 2008
The Physical Object
Paginationxiii, 258 p. :
Number of Pages258
ID Numbers
Open LibraryOL23196092M
ISBN 100121500136
ISBN 109780121500139
LC Control Number2008300668

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“To accommodate the high persistence and variability of volatility in financial time series, Calvet and Fisher developed the class of Markov-Switching Multifractal models. This book, which summarizes ten years of their research, is of great interest to researchers in asset pricing and essential reading for practitioners working on risk management or volatility /5(5). With all due respect to the other reviewers, there's not much point discussing how good a job this book does explaining multifractal volatility. It's the only book on that subject. I think it's more useful to describe why someone who doesn't already know what MV is might want to read this excellent book/5(5).   A large existing literature (e.g., Engle, ; Rossi, ) models volatility as an average of past shocks, possibly 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 Ratings: 0. “To accommodate the high persistence and variability of volatility in financial time series, Calvet and Fisher developed the class of Markov-Switching Multifractal models. This book, which summarizes ten years of their research, is of great interest to researchers in asset pricing and essential reading for practitioners working on risk management or volatility Price: $

The goal of Multifractal Volatility is to popularize the approach by presenting these exciting new developments to a wider audience. They emphasize both theoretical and empirical applications. “To accommodate the high persistence and variability of volatility in financial time series, Calvet and Fisher developed the class of Markov-Switching Multifractal models. This book, which summarizes ten years of their research, is of great interest to researchers in asset pricing and essential reading for practitioners working on risk management or volatility . Introduction Modeling Multifrequency Volatility The theme of this book is that a simple class of models provides a parsimonious description of the seemingly disparate aspects of financial market . A multifractal system is a generalization of a fractal system in which a single exponent (the fractal dimension) is not enough to describe its dynamics; instead, a continuous spectrum of exponents (the so-called singularity spectrum) is needed.. Multifractal .

Modern technology can be utilized to supply the book Multifractal Volatility: Theory, Forecasting, And Pricing (Academic Press Advanced Finance), By Laurent E. Calvet, Adlai J. Fisher in only soft file system that could be opened up every single time you really want and anywhere you require without bringing this Multifractal Volatility.   The goal of Multifractal Volatility is to popularize the approach by presenting these exciting new developments to a wider audience. They emphasize both theoretical and empirical applications, /5(2). 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 Cited by: "To accommodate the high persistence and variability of volatility in financial time series, Calvet and Fisher developed the class of Markov-Switching Multifractal models. This book, which summarizes ten .