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Statistics and Data Analysis for Financial Engineering (Springer Texts in Statistics) by David Ruppert, David S. Matteson is a nonfiction available to read on EtoBox.

What is Statistics and Data Analysis for Financial Engineering (Springer Texts in Statistics) about?

Financial engineers have access to enormous quantities of data but need powerful methods for extracting quantitative information, particularly about volatility and risks. Key features of this textbook are: illustration of concepts with financial markets and economic data, R Labs with real-data exercises, and integration of graphical and analytic methods for modeling and diagnosing modeling errors. Despite some overlap with the author's undergraduate textbook Statistics and Finance: An Introduction, this book differs from that earlier volume in several important aspects: it is graduate-level; computations and graphics are done in R; and many advanced topics are covered, for example, multivariate distributions, copulas, Bayesian computations, VaR and expected shortfall, and cointegration. The prerequisites are basic statistics and probability, matrices and linear algebra, and calculus. Some exposure to finance is helpful. David Ruppert is Andrew Schultz, Jr., Professor of Engineering and Professor of Statistical Science, School of Operations Research and Information Engineering, Cornell University, where he teaches statistics and financial engineering and is a member of the Program i

Who reads Statistics and Data Analysis for Financial Engineering (Springer Texts in Statistics)?

Author

David Ruppert, David S. Matteson

Publisher

Springer New York

Published

2011

Language

EN

ISBN

9781461427490

Category

nonfiction

Subjects

Business, Sociology, Finance