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Statistics of Financial Markets

Exercises and Solutions

  • Textbook
  • © 2013

Overview

  • Updated edition, now with exotic Options and more Quantlets
  • Strikes a balance between theoretical presentation and practical challenges
  • Offers excercises in option pricing, time series analysis and advanced quantitative statistical techniques in finance
  • Provides computational solutions calculated using R and Matlab
  • Includes supplementary material: sn.pub/extras

Part of the book series: Universitext (UTX)

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Table of contents (18 chapters)

  1. Selected Financial Applications

Keywords

About this book

Practice makes perfect. Therefore the best method of mastering models is working with them.

This book contains a large collection of exercises and solutions which will help explain the statistics of financial markets. These practical examples are carefully presented and provide computational solutions to specific problems, all of which are calculated using R and Matlab. This study additionally looks at the concept of corresponding Quantlets, the name given to these program codes and which follow the name scheme SFSxyz123.

The book is divided into three main parts, in which option pricing, time series analysis and advanced quantitative statistical techniques in finance is thoroughly discussed. The authors have overall successfully created the ideal balance between theoretical presentation and practical challenges.

Reviews

From the book reviews:

“This edition in total presents 18 chapters, four pages of ‘Symbols and Notations,’ and another four and a half pages are devoted to providing definitions to commonly used terminology. … this book is a useful supplement for students, professionals, and practitioners in the area of financial statistics and related fields. … All the chapters of the book are carefully structured with natural flow. It is an interesting and useful collection of exercises, teaching theory by solving the related problems.” (Technometrics, Vol. 55 (2), May, 2013)

Authors and Affiliations

  • Ladislaus von Bortkiewicz Chair of Stati, C.A.S.E. Centre for Applied Statistics a, Humboldt-Universität zu Berlin, Berlin, Germany

    Szymon Borak, Brenda López-Cabrera

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

    Wolfgang Karl Härdle

About the authors

Szymon Borak received his Ph.D. in Quantitative Finance and Statistics from Humboldt-Universität zu Berlin in 2008. His research focused on dynamic semi-parametric factor models applied to implied volatility structures and energy markets. Currently he is working as a quant analyst on risk management of structured financial products.

Wolfgang Karl Härdle is Professor of Statistics at the Humboldt-Universität zu Berlin and the Director of CASE – the Centre for Applied Statistics and Economics. He teaches quantitative finance and semi-parametric statistical methods. His research focuses on dynamic factor models, multivariate statistics in finance and computational statistics. He is an elected member of the ISI and an advisor to the Guanghua School of Management, Peking University and to National Central University, Taiwan.

Brenda López-Cabrera is Professor of Weather, Climate and Energy Analysis at Humboldt Universität zu Berlin and a researcher at CASE - Centre for Applied Statistics and Economics. She teaches courses on statistics of financial markets, statistical tools in finance and insurance, and advanced methods in quantitative finance. Her research interests are in applications within the field of statistical analysis of options, insurance and energy. Her focus is on economic risk of natural hazards, especially catastrophe bonds, weather and energy markets.

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