Although there are many books on mathematical finance, few deal with the
statistical aspects of modern data analysis as applied to financial
problems. This textbook fills this gap by addressing some of the most
challenging issues facing financial engineers. It shows how
sophisticated mathematics and modern statistical techniques can be used
in the solutions of concrete financial problems. Concerns of risk
management are addressed by the study of extreme values, the fitting of
distributions with heavy tails, the computation of values at risk (VaR),
and other measures of risk. Principal component analysis (PCA),
smoothing, and regression techniques are applied to the construction of
yield and forward curves. Time series analysis is applied to the study
of temperature options and nonparametric estimation. Nonlinear filtering
is applied to Monte Carlo simulations, option pricing and earnings
prediction. This textbook is intended for undergraduate students
majoring in financial engineering, or graduate students in a Master in
finance or MBA program. It is sprinkled with practical examples using
market data, and each chapter ends with exercises. Practical examples
are solved in the R computing environment. They illustrate problems
occurring in the commodity, energy and weather markets, as well as the
fixed income, equity and credit markets. The examples, experiments and
problem sets are based on the library Rsafd developed for the purpose of
the text. The book should help quantitative analysts learn and implement
advanced statistical concepts. Also, it will be valuable for researchers
wishing to gain experience with financial data, implement and test
mathematical theories, and address practical issues that are often
ignored or underestimated in academic curricula.
This is the new, fully-revised edition to the book Statistical Analysis
of Financial Data in S-Plus.
René Carmona is the Paul M. Wythes '55 Professor of Engineering and
Finance at Princeton University in the department of Operations Research
and Financial Engineering, and Director of Graduate Studies of the
Bendheim Center for Finance. His publications include over one hundred
articles and eight books in probability and statistics. He was elected
Fellow of the Institute of Mathematical Statistics in 1984, and of the
Society for Industrial and Applied Mathematics in 2010. He is on the
editorial board of several peer-reviewed journals and book series.
Professor Carmona has developed computer programs for teaching
statistics and research in signal analysis and financial engineering. He
has worked for many years on energy, the commodity markets and more
recently in environmental economics, and he is recognized as a leading
researcher and expert in these areas.
