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Applied Quantitative Finance

  • Wolfgang Karl Härdle
  • Cathy Yi-Hsuan Chen
  • Ludger Overbeck

Part of the Statistics and Computing book series (SCO)

Table of contents

  1. Front Matter
    Pages i-x
  2. Market Risk

    1. Front Matter
      Pages 1-1
    2. H. Herwartz, B. Pedrinha, F. H. C. Raters
      Pages 3-23
    3. M. R. Fengler, H. Herwartz, F. H. C. Raters
      Pages 25-37
    4. S. F. Huang, H. C. Lin, T. Y. Lin
      Pages 39-56
  3. Credit Risk

    1. Front Matter
      Pages 71-71
    2. L. Overbeck, M. Sokolova
      Pages 93-111
    3. R. S. Tsay, H. Zhu
      Pages 113-128
    4. M. Kalkbrener, L. Overbeck
      Pages 153-176
    5. Y. Chen, R. B. Chen, Q. He
      Pages 177-206
    6. Wolfgang Karl Härdle, K. F. Phoon, D. K. C. Lee
      Pages 223-244
  4. Dynamics Risk Measurement

    1. Front Matter
      Pages 245-245
    2. Ostap Okhrin, Alexander Ristig, Ya-Fei Xu
      Pages 247-277
    3. Wolfgang Karl Härdle, N. Hautsch, U. Pigorsch
      Pages 279-294
    4. S. Žiković
      Pages 295-308
    5. Wolfgang Karl Härdle, W. Wang, L. Zboňáková
      Pages 331-353
    6. M. Linton, E. G. S. Teo, E. Bommes, C. Y. Chen, Wolfgang Karl Härdle
      Pages 355-372
  5. Ostap Okhrin, Alexander Ristig, Ya-Fei Xu
    Pages E1-E1

About this book

Introduction

This volume provides practical solutions and introduces recent theoretical developments in risk management, pricing of credit derivatives, quantification of volatility and copula modeling. This third edition is devoted to modern risk analysis based on quantitative methods and textual analytics to meet the current challenges in banking and finance. It includes 14 new contributions and presents a comprehensive, state-of-the-art treatment of cutting-edge methods and topics, such as collateralized debt obligations, the high-frequency analysis of market liquidity, and realized volatility.

The book is divided into three parts: Part 1 revisits important market risk issues, while Part 2 introduces novel concepts in credit risk and its management along with updated quantitative methods. The third part discusses the dynamics of risk management and includes risk analysis of energy markets and for cryptocurrencies. Digital assets, such as blockchain-based currencies, have become popular b

ut are theoretically challenging when based on conventional methods. Among others, it introduces a modern text-mining method called dynamic topic modeling in detail and applies it to the message board of Bitcoins. 

The unique synthesis of theory and practice supported by computational tools is reflected not only in the selection of topics, but also in the fine balance of scientific contributions on practical implementation and theoretical concepts. This link between theory and practice offers theoreticians insights into considerations of applicability and, vice versa, provides practitioners convenient access to new techniques in quantitative finance. Hence the book will appeal both to researchers, including master and PhD students, and practitioners, such as financial engineers. The results presented in the book are fully reproducible and all quantlets needed for calculations are provided on an accompanying website.

The Quantlet platform quantlet.de, quantlet.c

om, 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 allows readers to reproduce the tables, pictures and calculations inside this Springer book.


Keywords

quantitative finance risk management market risk credit risk value at risk volatility systemic risk network risk default modeling copula dynamics risk measurement copula modelling time varying quantile lasso high-frequency data cryptocurrency portfolio quantitative methods

Editors and affiliations

  • Wolfgang Karl Härdle
    • 1
  • Cathy Yi-Hsuan Chen
    • 2
  • Ludger Overbeck
    • 3
  1. 1.C.A.S.E.—Center for Applied Statistics and EconomicsHumboldt-Universität zu BerlinBerlinGermany
  2. 2.School of Business and EconomicsHumboldt-Universität zu BerlinBerlinGermany
  3. 3.Department of MathematicsUniversity of GiessenGiessenGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-54486-0
  • Copyright Information Springer-Verlag GmbH Germany 2017
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-662-54485-3
  • Online ISBN 978-3-662-54486-0
  • Series Print ISSN 1431-8784
  • Series Online ISSN 2197-1706
  • Buy this book on publisher's site