Numerical Integration of Stochastic Differential Equations

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


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,
$$\frac{{\partial y}}{{\partial \tau }} = \frac{{{\partial ^2}y}}{{\partial {x^2}}}$$


Covariance Volatility Paral 


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  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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