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Description of  Statistical Models and Methods for Financial Markets (Springer Texts in Statistics)

0387778268 pdf The goal of Part I is to provide students in financial mathematics (or engi- neering) and mathematical (or computational) finance programs with a basic background in statistics. The statistical methods covered include linear regres- sion (Chapter 1) and extensions to generalized linear models and nonlinear regression (Chapter 4), multivariate analysis (Chapter 2), likelihood inference and Bayesian methods (Chapters 2 and 4), and time series analysis (Chapter 5). Applications of these methods to quantitative finance are given in Chap- ter 3 (portfolio theory) and Chapter 6 (time series models of asset returns and their volatilities). The presentation attempts to strike a balance between theory and applications. Each chapter describes software implementations of the statistical methods in R and MATLAB and illustrates their applications to financial data. As mentioned in the Preface, detailed instructions and sam- ple output of the statistical software in these illustrative examples can be downloaded from the book’s Website.