Statistics of Financial Markets

Statistics of Financial Markets offers a vivid yet concise introduction to the growing field of statistical application in finance. The reader will learn the basic methods of evaluating option contracts, analysing financial time series, selecting portfolios and managing risks making realistic assumptions of the market behaviour. The focus is both on the fundamentals of mathematical finance and financial time series analysis and on applications to given problems of financial markets, thus making the book the ideal basis for lecturers, seminars and crash courses on the topic.

For the third edition the book has been updated and extensively revised. Several new aspects have been included: new chapters on long memory models, copulae and CDO valuation.

Practical exercises have been added, the solutions of which are provided in the book by S. Borak, W. Härdle and B. Lopez Cabrera (2010) ISBN 978-3-642-11133-4.

“Both R and Matlab Code, together with the data, can be downloaded by clicking on the Additional Information tab labeled “R and Matlab Code,” which you will find on the right-hand side of the webpage.”

• ARIMA
• Differential Equations
• Discrete Time
• Financial Time Series
• Neural Networks
• Option Management
• Option Portfolios
• Probability Theroy
• Risk and Backtesting
• Stochastic Integrals
• Stochastic Processes
• quantitative finance

From the reviews of the third edition:

“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

“This is a well-written book on statistical aspects of finance, which starts from definitions of basic financial instruments and then develops both old and latest models and methods … . There is a very good coverage of stochastic volatility through GARCH models, bringing out both its strength, and weakness in the non-stationary case. … Discussions of most models and their assessment are supported with real data. … the style of writing is clear, precise, and rigorous.” (Jayanta K. Ghosh, International Statistical Review, Vol. 80 (3), 2012)

• FB Mathematik, TU Kaiserslautern, Kaiserslautern, Germany

  Jürgen Franke

• L.v.Bortkiewicz Chair of Statistics, C.A.S.E. Centre f. Appl. Stat. & Econ., Humboldt-Universität zu Berlin, Berlin, Germany

  Wolfgang Karl Härdle

• Inst. Statistique, Université Catholique de Louvain, Leuven-la-Neuve, Belgium

  Christian Matthias Hafner

Jürgen Franke is a professor of applied mathematical statistics at the University of Kaiserslautern, member of the graduate school ‘Mathematics as a Key Technology’, and since 2000 he has been an advisor to the Financial Mathematics Group of the Fraunhofer Institute for Industrial Mathematics, Kaiserslautern. His research focuses on nonlinear time series and nonparametric statistics with applications in financial time series and risk analysis.
Wolfgang Karl Härdle is a professor of statistics at the Humboldt-Universität zu Berlin and director of C.A.S.E. – the Centre for Applied Statistics and Economics.  He teaches quantitative finance and semiparametric statistical methods. His research focuses on
dynamic factor models, multivariate statistics in finance and computational statistics. He is an elected ISI member and advisor to the Guanghua School of Management, Peking University and to National Central University, Taiwan.
Christian Matthias Hafner is a professor of econometrics and statistics at the Université Catholique de Louvain. His work is mainly concerned with the applications of nonlinear time series and volatility models to financial markets.

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