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Mar 16

Numerical Simulation of Stochastic Differential Equations

Posted by abiao at 16:47 | Code » Matlab | Comments(1) | Reads(28030)
Often we have to face the problem of solving a stochastic differential equation, and even more often there is no analytic solution, in another words, numerical monte carlo simulation is applied. I don't need to write much about this topic as here is a fantastic paper on it already: An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations, in which the author builds around 10 MATLAB programs, and the topics covered include stochastic integration, the Euler–Maruyama method, Milstein’s method, strong and weak convergence, linear stability, and the stochastic chain rule.

M files:
Euler–Maruyama method: http://personal.strath.ac.uk/d.j.higham/em.m

Milstein’s method: http://personal.strath.ac.uk/d.j.higham/milstrong.m

more can be downloaded at here.

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Extremely cool as well as accurate, everything is in the right spot.
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