9781441919083 - Statistical Analysis of Financial Data in S-Plus (Springer Texts in Statistics) de Carmona, René (8 resultados)

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 anemphasis on robustness and non-parametric techniques. The applications include the term structure of interest rates, theconstruction of commodity forward curves, and nonparametric alternativesto 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, andnonlinear GARCH models and nonlinear filtering are applied to stochasticvolatility 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.

Paperback. Condición: Brand New. 2004 edition. 467 pages. 10.00x7.01x1.07 inches. In Stock.

Condición: Sehr gut. Zustand: Sehr gut | Seiten: 472 | Sprache: Englisch | Produktart: Bücher | 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.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The first book at the graduate textbook level to discuss analyzing financial data with S-PLUSIncludes supplementary material: sn.pub/extrasRequest lecturer material: sn.pub/lecturer-materialThis is the first book at the graduate .

Paperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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. 472 pp. Englisch.