Abstract
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.
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© 2010 Springer-Verlag Berlin Heidelberg
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Platen, E., Bruti-Liberati, N. (2010). Monte Carlo Simulation of SDEs. In: Numerical Solution of Stochastic Differential Equations with Jumps in Finance. Stochastic Modelling and Applied Probability, vol 64. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13694-8_11
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DOI: https://doi.org/10.1007/978-3-642-13694-8_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12057-2
Online ISBN: 978-3-642-13694-8
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