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  • Textbook
  • © 2011

Markov Decision Processes with Applications to Finance

  • Contains various applications with a particular view towards finance/insurance
  • Avoids many technical (e.g. measure theoretic) problems
  • The collection of topics is unique
  • Approach is problem-oriented and illustrated by many examples
  • Includes supplementary material: sn.pub/extras

Part of the book series: Universitext (UTX)

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-xvi
  2. Introduction and First Examples

    • Nicole Bäuerle, Ulrich Rieder
    Pages 1-9
  3. Finite Horizon Optimization Problems and Financial Markets

    1. Front Matter

      Pages 11-11
  4. Finite Horizon Optimization Problems and FinancialMarkets

    1. Theory of Finite Horizon Markov Decision Processes

      • Nicole Bäuerle, Ulrich Rieder
      Pages 13-57
    2. The Financial Markets

      • Nicole Bäuerle, Ulrich Rieder
      Pages 59-74
    3. Financial Optimization Problems

      • Nicole Bäuerle, Ulrich Rieder
      Pages 75-144
  5. Partially Observable Markov Decision Problems

    1. Front Matter

      Pages 145-145
    2. Partially Observable Markov Decision Processes

      • Nicole Bäuerle, Ulrich Rieder
      Pages 147-174
    3. Partially Observable Markov Decision Problems in Finance

      • Nicole Bäuerle, Ulrich Rieder
      Pages 175-189
  6. Infinite Horizon Optimization Problems

    1. Front Matter

      Pages 191-191
    2. Theory of Infinite Horizon Markov Decision Processes

      • Nicole Bäuerle, Ulrich Rieder
      Pages 193-242
    3. Piecewise Deterministic Markov Decision Processes

      • Nicole Bäuerle, Ulrich Rieder
      Pages 243-265
    4. Optimization Problems in Finance and Insurance

      • Nicole Bäuerle, Ulrich Rieder
      Pages 267-299
  7. Stopping Problems

    1. Front Matter

      Pages 301-301
    2. Theory of Optimal Stopping Problems

      • Nicole Bäuerle, Ulrich Rieder
      Pages 303-330
    3. Stopping Problems in Finance

      • Nicole Bäuerle, Ulrich Rieder
      Pages 331-343
  8. Appendix

    1. Front Matter

      Pages 345-345
    2. Tools from Analysis

      • Nicole Bäuerle, Ulrich Rieder
      Pages 347-354
    3. Tools from Probability

      • Nicole Bäuerle, Ulrich Rieder
      Pages 355-363
    4. Tools from Mathematical Finance

      • Nicole Bäuerle, Ulrich Rieder
      Pages 365-368

About this book

The theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its application by means of numerous examples, mostly taken from the fields of finance and operations research. By using a structural approach many technicalities (concerning measure theory) are avoided. They cover problems with finite and infinite horizons, as well as partially observable Markov decision processes, piecewise deterministic Markov decision processes and stopping problems.

The book presents Markov decision processes in action and includes various state-of-the-art applications with a particular view towards finance. It is useful for upper-level undergraduates, Master's students and researchers  in both applied probability and finance, and provides exercises (without solutions).

Reviews

From the reviews:

“This book presents Markov decision processes with general state and action spaces and includes various state-of-the-art applications that stem from finance and operations research. … very helpful, not only for graduate students, but also for researchers working in the field of MDPs and finance. The authors do not focus only on discrete-time MDPs, but provide the description of different classes of Markov models … . Each chapter ends with remarks, where the potential reader may find further hints concerning references.” (Anna Jaskiewicz, Zentralblatt MATH, Vol. 1236, 2012)

Authors and Affiliations

  • , Institute for Stochastics, Karlsruhe Institute of Technology, Karlsruhe, Germany

    Nicole Bäuerle

  • , Institute of Optimization and Operations, University of Ulm, Ulm, Germany

    Ulrich Rieder

About the authors

Nicole Bäuerle is full professor for Stochastics at the Karlsruhe Institute of Technology. Currently she is in the board of the Fachgruppe Stochastik and the DGVFM (Deutsche Gesellschaft für Versicherungs- und Finanzmathematik). She is editor of the journals "Stochastic Models" and "Mathematical Methods of Operations Research".

Ulrich Rieder is full professor for Optimization and Operations Research at the University of Ulm since 1980. He helped to establish a new program in applied mathematics at Ulm, called Wirtschaftsmathematik. From 1990-2008 he was editor-in-chief of "Mathematical Methods of Operations Research". He is editor of several journals in the areas of operations research and finance.

Bibliographic Information

Buy it now

Buying options

eBook USD 59.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 79.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access