Primozic, Tom (2011) Estimating expected first passage times using multilevel Monte Carlo algorithm. Masters thesis, oxford university.
PDF (mscmcf dissertation)
In this paper we devise a method of numerically estimating the expected first passage times of stochastic processes. We use Monte Carlo path simulations with Milstein discretisation scheme to approximate the solutions of scalar stochastic differential equations. To further reduce the variance of the estimated expected stopping time and improve computational efficiency, we use the multi-level Monte Carlo algorithm, recently developed by Giles (2008a), and other variance-reduction techniques. Our numerical results show significant improvements over conventional Monte Carlo techniques.
|Item Type:||Thesis (Masters)|
|Subjects:||H - N > Mathematics education|
|Research Groups:||Mathematical and Computational Finance Group|
|Deposited By:||Laura Auger|
|Deposited On:||13 Aug 2011 08:55|
|Last Modified:||29 May 2015 19:04|
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