Last edited by Kimi
Monday, May 4, 2020 | History

9 edition of Multifractal volatility found in the catalog.

Multifractal volatility

theory, forecasting, and pricing

by Laurent E. Calvet

  • 220 Want to read
  • 16 Currently reading

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

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

  • 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

    Given the fact that multifractal is a powerful tool for depicting volatility complexities in financial markets, Wei and Wang proposed a measurement method and used the ARFIMA models to model multifractal volatility Cited by: Presents a powerful new technique for forecasting volatility. Leads the reader intuitively from existing volatility techniques to the frontier of research in this field by top scholars at major universities. The first comprehensive book on multifractal .

    Multifractal Volatility: Theory, Forecasting, and Pricing: Laurent E. Calvet, Adlai J. Fisher: Books - 4/5(4). Series: Academic Press Advanced Finance. Most recent volume. Volume. Principles of Financial Engineering Poised midway between intuition, actual events, and financial mathematics, this book can be used to solve problems in risk management, taxation, regulation, and above all, pricing. Multifractal Volatility .

      [Read book] Multifractal Volatility: Theory Forecasting and Pricing (Academic Press Advanced. wemesoo Trending. Michael Jordan. Brooks Koepka trash talked Michael Jordan . Multifractal Volatility: Theory, Forecasting, and Pricing (Academic Press Advanced Finance) eBook: Laurent E. Calvet, Adlai J. Fisher: : Kindle Store/5(3).


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Multifractal volatility by Laurent E. Calvet Download PDF EPUB FB2

“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 Cited by: The first comprehensive book on multifractal techniques in finance, a cutting-edge field of research Show less Presents a powerful new technique for forecasting volatility.

“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.

Multifractal volatility book 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 Multifractal volatility book 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. In this book, the authors break the bar-rier and bring a completely fresh, unified and complete approach to volatility mod-eling.

During their graduate years at Yale under the supervision of Sterling Profes-sor, Benoˆıt Mandelbrot, the father of frac-tal geometry, they developed the origi-nal Multifractal File Size: 55KB. As recognized, book Multifractal Volatility: Theory, Forecasting, And Pricing (Academic Press Advanced Finance), By Laurent E.

Calvet, Adlai J. Fisher is well known as the home window to open the world. Downloadable (with restrictions).

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, ; Rossi, ) models volatility.

What is Multifractal Analysis?. The point of a multifractal analysis is to detect the multi in multifractal does multifractal analysis tie in with box counting?It all boils down to the distribution of pixel values in a digital is, to do a multifractal. 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, ; Rossi, ) models volatility Cited by: Leads the reader intuitively from existing volatility techniques to the frontier of research in this field by top scholars at major universities.

The first comprehensive book on multifractal techniques in. 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. The local volatility of the time series under study can be constructed using this algorithm, and the multifractal structure of the time series can be analyzed by using this local volatility.In this section, we will show a possible relationship between the multifractal parameters Δ h and Δ α with the volatility (present or future) and the errors in the forecast of asset prices.

Volatility is a measure Cited by: 8.