Now in its fifth edition, this book offers a detailed yet concise
introduction to the growing field of statistical applications in
finance. The reader will learn the basic methods for evaluating option
contracts, analyzing financial time series, selecting portfolios and
managing risks based on realistic assumptions about market behavior. The
focus is both on the fundamentals of mathematical finance and financial
time series analysis, and on applications to specific problems
concerning financial markets, thus making the book the ideal basis for
lectures, seminars and crash courses on the topic. All numerical
calculations are transparent and reproducible using quantlets.
For this new edition the book has been updated and extensively revised
and now includes several new aspects such as neural networks, deep
learning, and crypto-currencies. Both R and Matlab code, together with
the data, can be downloaded from the book's product page and the
Quantlet platform.
The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an
integrated QuantNet environment consisting of different types of
statistics-related documents and program codes. Its goal is to promote
reproducibility and offer a platform for sharing validated knowledge
native to the social web. QuantNet and the corresponding Data-Driven
Documents-based visualization allow readers to reproduce the tables,
pictures and calculations inside this Springer book.
"This book provides an excellent introduction to the tools from
probability and statistics necessary to analyze financial data. Clearly
written and accessible, it will be very useful to students and
practitioners alike."
Yacine Ait-Sahalia, Otto Hack 1903 Professor of Finance and Economics,
Princeton University
