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Palgrave Macmillan

Advanced Simulation-Based Methods for Optimal Stopping and Control

With Applications in Finance

  • Book
  • © 2018

Overview

Authors:
  1. Denis Belomestny

    1. Faculty of Mathematics, Duisburg-Essen University, Essen, Germany

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    You can also search for this author in PubMed   Google Scholar

  2. John Schoenmakers

    1. Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany

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    You can also search for this author in PubMed   Google Scholar

  • Presents the very latest applications of probability modelling to derivatives pricing and risk management

  • Brings new approaches and applications to the quant’s toolkit - Monte Carlo simulations are the bedrock of much of the quantitative practitioners work and this book presents a core quant topic

  • Leading researchers Schoenmakers and Belomestny are well regarded for their research in stochastics and probability theory – this book will be well received by the community

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-xvi
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  2. Introduction

    • Denis Belomestny, John Schoenmakers
    Pages 1-9

  3. Monte Carlo Techniques

    1. Front Matter

      Pages 11-11
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    2. Elementary Monte Carlo Methods

      • Denis Belomestny, John Schoenmakers
      Pages 13-32

    3. Variance Reduction for SDEs

      • Denis Belomestny, John Schoenmakers
      Pages 33-53

    4. Multilevel Methods

      • Denis Belomestny, John Schoenmakers
      Pages 55-75

  4. Primal Methods for Optimal Stopping and Control

    1. Front Matter

      Pages 77-77
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    2. General Problem Setups

      • Denis Belomestny, John Schoenmakers
      Pages 79-82

    3. Primal Approximation Methods for Optimal Stopping

      • Denis Belomestny, John Schoenmakers
      Pages 83-96

    4. Stochastic Policy Iteration Methods

      • Denis Belomestny, John Schoenmakers
      Pages 97-134

    5. Regression Methods for Markovian Control Problems

      • Denis Belomestny, John Schoenmakers
      Pages 135-158

  5. Dual Methods for Optimal Stopping and Control

    1. Front Matter

      Pages 159-159
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    2. Duality for Optimal Stopping

      • Denis Belomestny, John Schoenmakers
      Pages 161-175

    3. Duality for Multiple Stopping

      • Denis Belomestny, John Schoenmakers
      Pages 177-187

    4. Dual Methods for General Optimal Control

      • Denis Belomestny, John Schoenmakers
      Pages 189-199

    5. Dual Monte Carlo Algorithms for Optimal Stopping

      • Denis Belomestny, John Schoenmakers
      Pages 201-285

    6. Pricing Bermudan Options via Consumption Processes

      • Denis Belomestny, John Schoenmakers
      Pages 287-311

    7. Dual Monte Carlo Algorithms for Optimal Control

      • Denis Belomestny, John Schoenmakers
      Pages 313-334

  6. Back Matter

    Pages 335-364
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Keywords

About this book

This is an advanced guide to optimal stopping and control, focusing on advanced Monte Carlo simulation and its application to finance. Written for quantitative finance practitioners and researchers in academia, the book looks at the classical simulation based algorithms before introducing some of the new, cutting edge approaches under development.

Authors and Affiliations

  • Faculty of Mathematics, Duisburg-Essen University, Essen, Germany

    Denis Belomestny

  • Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany

    John Schoenmakers

About the authors

Dr. John Schoenmakers (Berlin, Germany) is Deputy head of the Stochastic Algorithms and Nonparametric statistics research group at the Weierstrass Institute for Applied Analysis and Stochastics. His fields of interest include advanced modeling of equity and interest rate term structures, pricing and structuring of high dimensional callable derivatives, and general risk measures, stochastic modeling, Monte Carlo methods and many more. He has held the position of Visiting Professor at HU Berlin, and is on the editorial board of the Journal of Computational Finance, Monte Carlo Methods and its Applications, and International Journal of Portfolio Analysis and Management.

Dr. Denis Belomestny (Duisburg, Germany) is Senior Researcher at Weierstrass Institute for Applied Analysis and Stochastics, where he works on the Statistical Data Analysis and Applied Mathematical Finance project. Previously, he was a researcher at the Institute for Applied Mathematics at Bonn University. His research interests include nonparametric statistics, stochastic processes and financial mathematics, and his research is published in a number of peer reviewed publications.

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