Overview
- Examples using financial markets and economic data illustrate important concepts
- R Labs with real-data exercises give students practice in data analysis
- Integration of graphical and analytic methods for model selection and model checking quantify and help mitigate risks due to modeling errors and uncertainty
- Includes supplementary material: sn.pub/extras
- Request lecturer material: sn.pub/lecturer-material
Part of the book series: Springer Texts in Statistics (STS)
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Table of contents (21 chapters)
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Front Matter
Keywords
About this book
<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>
Reviews
From the reviews:
“Book under review is aimed at Master’s students in a financial engineering program and spans the gap between some very basic finance concepts and some very advanced statistical concepts … . The book is evidently intended as, and is best approached as, a kind of working text, giving students the opportunity to work in detail through a variety of examples. The substantial chapters on regression and time series are particularly helpful in this regard. There is lots of useful R code and many example analyses.” (R. A. Maller, Mathematical Reviews, Issue 2012 d)Authors and Affiliations
About the author
<div style="MARGIN: 0in 0in 0pt; LINE-HEIGHT: normal">Financial Engineering. His research areas include asymptotic theory, semiparametric regression, functional data analysis, biostatistics, model calibration, measurement error, and astrostatistics. Professor Ruppert received his PhD in Statistics at Michigan State University. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics and won the Wilcoxon prize. He is Editor of the <em>Electronic Journal of Statistics</em>, former Editor of the Institute of Mathematical Statistics' <em>Lecture Notes--Monographs Series</em>, and former Associate Editor of several major statistics journals. Professor Ruppert has published over 100 scientific papers and four books: <em>Transformation and Weighting in Regression</em>, <em>Measurement Error in Nonlinear Models</em>, <em>Semiparametric Regression</em>, and <em>Statistics and Finance: An Introduction</em>.</div>
Bibliographic Information
Book Title: Statistics and Data Analysis for Financial Engineering
Authors: David Ruppert
Series Title: Springer Texts in Statistics
DOI: https://doi.org/10.1007/978-1-4419-7787-8
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media, LLC 2011
Softcover ISBN: 978-1-4614-2749-0Published: 27 December 2012
eBook ISBN: 978-1-4419-7787-8Published: 08 November 2010
Series ISSN: 1431-875X
Series E-ISSN: 2197-4136
Edition Number: 1
Number of Pages: XXII, 638
Topics: Statistics for Business, Management, Economics, Finance, Insurance