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Statistics and Data Analysis for Financial Engineering by David Ruppert [Repost]
![Statistics and Data Analysis for Financial Engineering by David Ruppert [Repost]](https://pixhost.icu/avaxhome/9c/9d/00379d9c.jpeg)
Statistics and Data Analysis for Financial Engineering (Springer Texts in Statistics) by David Ruppert
English | Jan. 2, 2013 | ISBN: 1441977864, 1461427495 | 662 Pages | PDF | 11 MB
English | Jan. 2, 2013 | ISBN: 1441977864, 1461427495 | 662 Pages | PDF | 11 MB
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.