Monte Carlo Simulation of SDEs

  • Eckhard PlatenEmail author
  • Nicola Bruti-Liberati
Part of the Stochastic Modelling and Applied Probability book series (SMAP, volume 64)


This chapter introduces what is commonly known as Monte Carlo simulation for stochastic differential equations. We explain that Monte Carlo simulation is a much simpler task than scenario simulation, discussed in the previous chapters. A weak convergence criterion will be introduced that allows us to classify various discrete-time approximations and numerical schemes for the purpose of Monte Carlo simulation. For simplicity, we focus on the case without jumps in this introductory chapter. The case with jumps is more complicated and will be described in Chaps. 12 and 13.


Monte Carlo Simulation Weak Convergence Time Step Size Euler Scheme Weak Order 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.School of Finance and Economics, Department of Mathematical SciencesUniversity of Technology, SydneyBroadwayAustralia

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