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Statistics and Data Analysis for Financial Engineering
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 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 An Introduction, this book differs from that earlier volume in several important 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.
The prerequisites are basic statistics and probability, matrices and linear algebra, and calculus.
Some exposure to finance is helpful.
638 pages, Hardcover
First published November 1, 2010
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Displaying 1 - 2 of 2 reviews
December 29, 2014
Great text for someone with prior background in Probability Theory and Calculus. A crisp, to-the-point text book for financial econometrics.
July 31, 2012
This book broadly covers many statistical techniques applied in finance. Most likely the audience for this book is for students in Quant Finance programs learning some statistics techniques. I guess it succeeds in that purpose. But for researchers, statisticians, or practitioners there is not enough depth.
I rated this book 2 stars rather than 1 star, because I do believe Ruppert did a good job introducing difficult topics, for example the Bayesian methods. But generally, this book and his other undergraduate version "Statistics and Finance" are not worth reading unless you are completely new to a topic. That being said, some of Ruppert's other books are quite nice, for example "Semiparametric Regression".
I rated this book 2 stars rather than 1 star, because I do believe Ruppert did a good job introducing difficult topics, for example the Bayesian methods. But generally, this book and his other undergraduate version "Statistics and Finance" are not worth reading unless you are completely new to a topic. That being said, some of Ruppert's other books are quite nice, for example "Semiparametric Regression".
Displaying 1 - 2 of 2 reviews