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Statistics and Finance: An Introduction
 
 
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Statistics and Finance: An Introduction [Hardcover]

David Ruppert (Author)
3.3 out of 5 stars  See all reviews (6 customer reviews)

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Book Description

0387202706 978-0387202709 March 30, 2004 1st
This book emphasizes the applications of statistics and probability to finance. The basics of these subjects are reviewed and more advanced topics in statistics, such as regression, ARMA and GARCH models, the bootstrap, and nonparametric regression using splines, are introduced as needed. The book covers the classical methods of finance and it introduces the newer area of behavioral finance. Applications and use of MATLAB and SAS software are stressed. The book will serve as a text in courses aimed at advanced undergraduates and masters students. Those in the finance industry can use it for self-study.

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Editorial Reviews

Review

From the reviews: "The inherent interaction of statistical and financial modeling makes this book a very useful and motivating instrument with which to introduce students from engineering, mathematics, statistics and economics to study statistics and/or finance." Short Book Reviews of the International Statistical Institute, December 2004 "This book will be on my list of study book sfor 2005. If you have any interest or involvement with statistics in financial applications, I recommend this book to you." Technometrics, May 2005 "...The book is well-written and clear....the clear writing with illustrative examples and pictures strongly recommend the book as a basis for finance-motivated statistics classes at the undergraduate level." SIAM Review, Vol. 47, No. 2 "David Ruppert’s … discusses computation in SAS and MATLAB. … the book is very well written and clear. … the clear writing and illustrative examples and pictures strongly recommend the book as a basis for finance-motivated statistics classes at the undergraduate level." (Ronnie Sircar, SIAM Review, Vol. 47 (2), 2005) "That statistical methods are becoming more important in finance is further evidenced by this book from a statistician who has written some excellent … . For the statistician, this is a very good book to peruse, because it presumes no background in finance. Here the financial concepts are fully explained … . book with a considerable statistical content. … will be on my list of study books for 2005. If you have any interest in or involvement with statistics in financial applications, I recommend this book to you." (Technometrics, Vol. 47 (2), May, 2005) "This book emphasizes the application of probability and statistics to finance by studying statistical models of financial markets … . The emphasis is on concepts rather than mathematics, and several examples are given as illustration. … . This book should be a valuable resource for those who are interested in the applications of probability and statistics to finance, and I believe that it will be a very useful addition to any scholarly library." (Theofanis Sapatinas, Journal of the Royal Statistical Society Series A, Vol. 168 (2), 2005) "The inherent interaction of statistical and financial modeling makes this book a very useful and motivating instrument with which to introduce students from engineering, mathematics, statistics and economics to study statistics and/or finance. … the manuscript succeeds in covering relatively recent topics from statistics and finance, like the bootstrap, penalized splines, some VaR estimation models and behavioural finance. … Students having gained confidence with the material of this book can also be expected to be ready for advanced topics … ." (F. Trojani, Short Book Reviews International Statistical Institute, Vol. 24 (3), 2004) "...Ruppert's book succeeds at presenting this classic material in a concises, readable way that is suitable for a wide audience including undergraduate business, economics, and statistics majors, MBA students, and master's level engineering students." Journal of the American Statistical Association, June 2006 "The book under review is about statistical concepts as applied to financial theory. … The book provides a coherent introduction of how to handle financial data by means of statistics. … Due to a very nontechnical language and a lot of examples using SAS or MATLAB the book is suitable for undergraduates and master students in statistics, applied mathematics and finance. But it can also be used for self-study." (Karsten Webel, Statistical Papers, Vol. 47, 2006) "As the title indicates, this is a textbook on Statistics and its application in Finance. … The book is well written … . It is … suited as a text for an introduction to Statistics and Finance in a more applied department, e.g. Industrial Engineering or Operations Research. … it is a well written book, that nicely illustrates the interplay between Statistics and Finance. It is also useful as a source for additional teaching material." (T. de Wet, SASA News, June, 2005) "The material of the book is organized in 14 chapters. … Students will love the conclusive summaries best … . David Ruppert knows how to hold the interest of his readers. Often little anecdotes on the discovery of new results are included and the data are chosen such that delightful features can be detected. So instructors can also use the book in a pure statistics course … . The topic is hot since ‘everyone is interested in money’." (Norman Fickel, Allgemeines Statistisches Archiv, Vol. 89, 2005) "This is a very lucid textbook emphasizing the application of statistics and probability to finance. The material is always backed up by realistic examples from finance. … Indeed following these may serve as a quick and easy way of learning the basics of these softwares. Short bibliographic notes at the end of each chapter are extremely useful." (Arup Bose, Sankhya, Vol. 67 (1), 2005) "The book ‘Statistics and Finance’ by David Ruppert discusses many financial models. … This book is appropriate for the third and fourth year undergraduate and master level courses. It will be useful to the practicing financial engineer. It assumes some background in probability and statistics. The book is interesting from both the statistical modeling and the finance perspectives." (Qin Lu, Zentralblatt MATH, Vol. 1049, 2004) "The text book emphazises the applications of statistics and probability to finance. … The book will serve as a text in courses aimed at advanced undergraduates and masters students in statistics, engineering, and applied mathematics as well as quantitatively oriented MBA students. Those in the finance industry wishing to know more statistics could also use it for self-study." (Zentralblatt für Didaktik der Mathematik, July, 2004)

From the Back Cover

This textbook emphasizes the applications of statistics and probability to finance. Students are assumed to have had a prior course in statistics, but no background in finance or economics. The basics of probability and statistics are reviewed and more advanced topics in statistics, such as regression, ARMA and GARCH models, the bootstrap, and nonparametric regression using splines, are introduced as needed. The book covers the classical methods of finance such as portfolio theory, CAPM, and the Black-Scholes formula, and it introduces the somewhat newer area of behavioral finance. Applications and use of MATLAB and SAS software are stressed. The book will serve as a text in courses aimed at advanced undergraduates and masters students in statistics, engineering, and applied mathematics as well as quantitatively oriented MBA students. Those in the finance industry wishing to know more statistics could also use it for self-study. David Ruppert is the Andrew Schultz, Jr. Professor of Engineering, School of Operations Research and Industrial Engineering, Cornell University. He received a PhD in Statistics from Michigan State University in 1977 and taught for ten years in the Department of Statistics at the University of North Carolina at Chapel Hill. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics and a winner of the Wilcoxon Prize for the best practical applications paper in Technometrics. He is former Editor of the Institute of Mathematical Statistics's Lecture Notes-Monographs Series, former Associate Editor of The American Statistician and The Annals of Statistics, and currently Associate Editor of Biometrics and The Journal of the American Statistical Associate. He has published over 80 scientific papers and three books, Transformation and Weighting in Regression, Measurement Error in Nonlinear Models, and Semiparametric Regression.

Product Details

  • Hardcover: 482 pages
  • Publisher: Springer; 1st edition (March 30, 2004)
  • Language: English
  • ISBN-10: 0387202706
  • ISBN-13: 978-0387202709
  • Product Dimensions: 9.3 x 6.4 x 1.1 inches
  • Shipping Weight: 1.8 pounds (View shipping rates and policies)
  • Average Customer Review: 3.3 out of 5 stars  See all reviews (6 customer reviews)
  • Amazon Best Sellers Rank: #362,145 in Books (See Top 100 in Books)

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6 Reviews
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Average Customer Review
3.3 out of 5 stars (6 customer reviews)
 
 
 
 
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Most Helpful Customer Reviews

20 of 23 people found the following review helpful:
5.0 out of 5 stars great book, especially for statisticians, July 27, 2006
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This review is from: Statistics and Finance: An Introduction (Hardcover)
This book is an ambitious and unique combination of stat and finance - and because of the very close relationship of the two areas, this book is excellent and useful for 1) statisticians who want to learn financial modeling; and 2) financial analysts who need to understand the underlying stat concepts at a relatively advanced level. It is generally well-written and the author provides clear explanation on many finance theories.
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7 of 7 people found the following review helpful:
4.0 out of 5 stars Great book!, July 3, 2008
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This review is from: Statistics and Finance: An Introduction (Hardcover)
I am a post graduate student in Finland. I've been trying to find a suitable book which would take me a step further after Luenberger's Investment Science (Cochrane's book is a too large leap for me). This excellent book which does just that. It covers interesting topics such as Michaud's resampling, volatility surfaces and interest rate models. The treatment of various topics is rather short though. However, after each chapter Ruppert has a bibliography where he recommends additional reading for each subject.

Text is extremely readable and even though I am not in MIT like some reviewers (possibly meaning that I might not be that smart) I found the text easy to understand and the examples in the book really help to elaborate the text. If you want some light reading that tells you a little about a lot, this is the book for you.


In addition, you can find some nice R code for the book which a little bit of googling.
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7 of 13 people found the following review helpful:
1.0 out of 5 stars Avoid Like Michael Jackson at a Chuck E. Cheese, April 22, 2007
This review is from: Statistics and Finance: An Introduction (Hardcover)
Ruppert tries to cover too many topics in too few pages. As a result, the treatment of topics is perfunctory at best, and the exercises are almost nonexistent. If you really want to learn the material, look at the table of contents, and for each chapter, buy a separate textbook.
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Inside This Book (learn more)
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Estimate Error, Journal of Finance, Bibliographic Notes, Corrected Total, Squares Square, Parameter Estimates Parameter Standard Variable, Adj R-Sq, Coeff Var, Itl Intercept, Dependent Mean, Upper Saddle River, Total R-Square, Cambridge University Press, Journal of Financial Economics, Standard Approx Variable, Irrational Exuberance, Model R-Square, Princeton University Press, Approx Approximate, Capital Ideas, Constant Estimate, Financial Data Analysis, Ford Motor Company, Free Press
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