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. 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 TOC:Introduction.- Probability and Statistical Models.-
Returns.- Time Series Models.- Portfolio Theory.- Regression.- The Capital Asset Pricing
Model.- Options Pricing.- Fixed Income Securities.- Resampling.- Value-at-Risk.- GARCH models.-
Nonparametric Regression and Splines.- Behavioral Finance.
