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Numerical Approximations of Stochastic Differential Equations with Non-Globally Lipschitz Continuous Coefficients
 
Martin Hutzenthaler University of Duisburg-Essen, Essen, North Rhine-Westphalia, Germany
Arnulf Jentzen ETH Zurich, Zurich, Switzerland
Front Cover for Numerical Approximations of Stochastic Differential Equations with Non-Globally Lipschitz Continuous Coefficients
Available Formats:
Electronic ISBN: 978-1-4704-2278-3
Product Code: MEMO/236/1112.E
List Price: $76.00
MAA Member Price: $68.40
AMS Member Price: $45.60
Front Cover for Numerical Approximations of Stochastic Differential Equations with Non-Globally Lipschitz Continuous Coefficients
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  • Front Cover for Numerical Approximations of Stochastic Differential Equations with Non-Globally Lipschitz Continuous Coefficients
  • Back Cover for Numerical Approximations of Stochastic Differential Equations with Non-Globally Lipschitz Continuous Coefficients
Numerical Approximations of Stochastic Differential Equations with Non-Globally Lipschitz Continuous Coefficients
Martin Hutzenthaler University of Duisburg-Essen, Essen, North Rhine-Westphalia, Germany
Arnulf Jentzen ETH Zurich, Zurich, Switzerland
Available Formats:
Electronic ISBN:  978-1-4704-2278-3
Product Code:  MEMO/236/1112.E
List Price: $76.00
MAA Member Price: $68.40
AMS Member Price: $45.60
  • Book Details
     
     
    Memoirs of the American Mathematical Society
    Volume: 2362015; 99 pp
    MSC: Primary 60; Secondary 65;

    Many stochastic differential equations (SDEs) in the literature have a superlinearly growing nonlinearity in their drift or diffusion coefficient. Unfortunately, moments of the computationally efficient Euler-Maruyama approximation method diverge for these SDEs in finite time.

    This article develops a general theory based on rare events for studying integrability properties such as moment bounds for discrete-time stochastic processes. Using this approach, the authors establish moment bounds for fully and partially drift-implicit Euler methods and for a class of new explicit approximation methods which require only a few more arithmetical operations than the Euler-Maruyama method. These moment bounds are then used to prove strong convergence of the proposed schemes. Finally, the authors illustrate their results for several SDEs from finance, physics, biology and chemistry.

  • Table of Contents
     
     
    • Chapters
    • 1. Introduction
    • 2. Integrability properties of approximation processes for SDEs
    • 3. Convergence properties of approximation processes for SDEs
    • 4. Examples of SDEs
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Volume: 2362015; 99 pp
MSC: Primary 60; Secondary 65;

Many stochastic differential equations (SDEs) in the literature have a superlinearly growing nonlinearity in their drift or diffusion coefficient. Unfortunately, moments of the computationally efficient Euler-Maruyama approximation method diverge for these SDEs in finite time.

This article develops a general theory based on rare events for studying integrability properties such as moment bounds for discrete-time stochastic processes. Using this approach, the authors establish moment bounds for fully and partially drift-implicit Euler methods and for a class of new explicit approximation methods which require only a few more arithmetical operations than the Euler-Maruyama method. These moment bounds are then used to prove strong convergence of the proposed schemes. Finally, the authors illustrate their results for several SDEs from finance, physics, biology and chemistry.

  • Chapters
  • 1. Introduction
  • 2. Integrability properties of approximation processes for SDEs
  • 3. Convergence properties of approximation processes for SDEs
  • 4. Examples of SDEs
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