Statistics and Data Analysis for Financial Engineering PDF
by David Ruppert
Part of the Springer Texts in Statistics series
Description
<div style="MARGIN: 0in 0in 0pt; LINE-HEIGHT: normal">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 <em>Statistics and Finance: An Introduction</em>, 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. </div>
<div style="MARGIN: 0in 0in 0pt; LINE-HEIGHT: normal">The prerequisites are basic statistics and probability, matrices and linear algebra, and calculus.</div>
<div style="MARGIN: 0in 0in 0pt; LINE-HEIGHT: normal">Some exposure to finance is helpful.</div>
Information
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Download - Immediately Available
- Format:PDF
- Publisher:Springer New York
- Publication Date:08/11/2010
- Category:
- ISBN:9781441977878
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Information
-
Download - Immediately Available
- Format:PDF
- Publisher:Springer New York
- Publication Date:08/11/2010
- Category:
- ISBN:9781441977878
