Statistics and Finance: An Introduction (Springer Texts in Statistics)

Description: 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.' 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 books for 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 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. It is a book with a considerable statistical content. It 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.

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