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Fat-Tailed and Skewed Asset Return Distributions - Christian Menn

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        Présentation Fat - Tailed And Skewed Asset Return Distributions de Christian Menn Format Relié

         - Livre Anglais

        Livre Anglais - Christian Menn - 01/07/2005 - Relié - Langue : Anglais

        . .

      • Auteur(s) : Christian Menn - Frank J Fabozzi - Svetlozar T Rachev
      • Editeur : John Wiley & Sons
      • Langue : Anglais
      • Parution : 01/07/2005
      • Format : Moyen, de 350g à 1kg
      • Nombre de pages : 384.0
      • Nombre de livres : 1
      • Expédition : 1280
      • ISBN : 9780471718864



      • Résumé :
        While mainstream financial theories and applications assume that asset returns are normally distributed, overwhelming empirical evidence shows otherwise. Yet many professionals don't appreciate the highly statistical models that take this empirical evidence into consideration. Fat-Tailed and Skewed Asset Return Distributions examines this dilemma and offers readers a less technical look at how portfolio selection, risk management, and option pricing modeling should and can be undertaken when the assumption of a non-normal distribution for asset returns is violated. Topics covered in this comprehensive book include an extensive discussion of probability distributions, estimating probability distributions, portfolio selection, alternative risk measures, and much more. Fat-Tailed and Skewed Asset Return Distributions provides a bridge between the highly technical theory of statistical distributional analysis, stochastic processes, and econometrics of financial returns and real-world risk management and investments....

        Biographie:
        SVETLOZAR T. RACHEV, PhD, DR. SCI, is currently Chair-Professor at the University of Karlsruhe in the School of Economics and Business Engineering and Professor Emeritus at the University of California. He is also the founder of Bravo Risk Management Group and Chief Scientist of FinAnalytica.

        CHRISTIAN MENN, DR. RER. POL., is Hochschulassistent at the Chair of Statistics, Econometrics and Mathematical Finance at the University of Karlsruhe. Currently, he is a Visiting Scientist at the School of Operations Research and Industrial Engineering at Cornell University as a postdoctoral fellow.

        FRANK J. FABOZZI, PhD, CFA, CPA, is the Frederick Frank Adjunct Professor of Finance at Yale University's School of Management. He is also a Fellow of the International Center for Finance at Yale University. Prior to joining the Yale faculty, Fabozzi was a visiting professor of finance in the Sloan School at MIT. Fabozzi has authored and edited many acclaimed books in finance and is also the Editor of the Journal of Portfolio Management.

        ...

        Sommaire:
        Preface.

        About the Authors.

        Chapter 1: Introduction.

        PART ONE: Probability and Statistics.

        Chapter 2: Discrete Probability Distributions.

        Chapter 3: Continuous Probability Distributions.

        Chapter 4: Describing a Probability Distribution Function: Statistical Moments and Quantiles.

        Chapter 5: Joint Probability Distributions.

        Chapter 6: Copulas.

        Chapter 7: Stable Distributions.

        Chapter 8: Estimation Methodologies.

        PART TWO: Stochastic Processes.

        Chapter 9: Stochastic Processes in Discrete Time and Time Series Analysis.

        Chapter 10: Stochastic Processes in Continuous Time.

        PART THREE: Portfolio Selection.

        Chapter 11: Equity and Bond Return Distributions.

        Chapter 12: Risk Measures and Portfolio Selection.

        Chapter 13: Risk Measures in Portfolio Optimization and Performance Measures.

        PART FOUR: Risk Management.

        Chapter 14: Market Risk.

        Chapter 15: Credit Risk.

        Chapter 16: Operational Risk.

        PART FIVE: Option Pricing.

        Chapter 17: Introduction to Option Pricing and the Binomial Model.

        Chapter 18: Black-Scholes Option Pricing Model.

        Chapter 19: Extension of the Black-Scholes Model and Alternative Approaches.

        INDEX.

        ...

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