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Numerical Integration of Stochastic Differential Equations

  • Rüdiger Seydel
Part of the Universitext book series (UTX)

Abstract

This chapter provides an introduction into the numerical integration of stochastic differential equations (SDEs). Again X t denotes a stochastic process and solution of an SDE,
$$\frac{{\partial y}}{{\partial \tau }} = \frac{{{\partial ^2}y}}{{\partial {x^2}}}$$

Keywords

Monte Carlo Simulation Stochastic Differential Equation Wiener Process American Option Euler Scheme 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    An autonomous differential equation does not explicitly depend on the independent variable, here a(X t ) rather than a(Xt, t). The standard Model 1.13 of the stock market is autonomous for constant μ and σ.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Rüdiger Seydel
    • 1
  1. 1.Institute of MathematicsUniversity of KölnKölnGermany

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