Statistical Analysis Of Financial Data In S-Plus

This book develops the use of statistical data analysis in finance and it usesthe statistical software environment of SPLUS as a vehicle for presentingpractical... » 

This book develops the use of statistical data analysis in finance and it usesthe statistical software environment of SPLUS as a vehicle for presentingpractical implementations from financial engineering. It is divided into threeparts. Part I Exploratory Data Analysis reviews the most commonly usedmethods of statistical data exploration. Its originality lies in theintroduction of tools for the estimation and simulation of heavy taildistributions and copulas the computation of measures of risk and theprincipal component analysis of yield curves. Part II Regression introducesmodern regression concepts with an emphasis on robustness and nonparametrictechniques. The applications include the term structure of interest rates theconstruction of commodity forward curves and nonparametric alternatives to theBlack Scholes option pricing paradigm. Part III Time Series and State SpaceModels is concerned with theories of time series and of state space models.Linear ARIMA models are applied to the analysis of weather derivatives Kalmanfiltering is applied to public company earnings prediction and nonlinear GARCHmodels and nonlinear filtering are applied to stochastic volatility models. Thebook is aimed at undergraduate students in financial engineering masterstudents in finance and MBAs and to practitioners with financial dataanalysis concerns. TOCUnivariate Exploratory Data Analysis. Multivariate DataExploration. Parametric Regression. Local and Nonparametric Regression. TimeSeries Models AR MA ARMA and all that. Multivariate Linear Systems andFiltering. Nonlinear Time Series. «