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Autor(en): 
  • René Carmona
  • Statistical Analysis of Financial Data in S-Plus 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Dezember 2011  
    Genre:  Wirtschaft / Recht 
     
    Actuarial Mathematics / Actuarial science / Actuarial Sciences / Applications of Mathematics / B / Business Mathematics / Computational Mathematics and Numerical Analysis / Computer mathematics / Economics, finance, business & management / Economics, Mathematical / Finance & accounting / Insurance & actuarial studies / Management science / Mathematics and Statistics / Numerical analysis / Probability & statistics / Quantitative Finance / Statistics
    ISBN:  9781441919083 
    EAN-Code: 
    9781441919083 
    Verlag:  Springer Nature EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Springer Texts in Statistics  
    Dimensionen:  H 254 mm / B 178 mm / D  
    Gewicht:  891 gr 
    Seiten:  455 
    Illustration:  XVI, 455 p. 138 illus., schwarz-weiss Illustrationen 
    Zus. Info:  Previously published in hardcover 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book develops the use of statistical data analysis in finance, and it uses the statistical software environment of S-PLUS as a vehicle for presenting practical implementations from financial engineering. It is divided into three parts. Part I, Exploratory Data Analysis, reviews the most commonly used methods of statistical data exploration. Its originality lies in the introduction of tools for the estimation and simulation of heavy tail distributions and copulas, the computation of measures of risk, and the principal component analysis of yield curves. Part II, Regression, introduces modern regression concepts with an emphasis on robustness and non-parametric techniques. The applications include the term structure of interest rates, the construction of commodity forward curves, and nonparametric alternatives to the Black Scholes option pricing paradigm. Part III, Time Series and State Space Models, is concerned with theories of time series and of state space models. Linear ARIMA models are applied to the analysis of weather derivatives, Kalman filtering is applied to public company earnings prediction, and nonlinear GARCH models and nonlinear filtering are applied to stochastic volatility models. The book is aimed at undergraduate students in financial engineering, master students in finance and MBA's, and to practitioners with financial data analysis concerns.

      



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