Tata Institute of Fundamental Research
Multilevel Monte Carlo Path Simulation
Student Seminar
Speaker:
Ankush Agarwal
Organiser:
Gugan Thoppe
Date:
Friday, 5 Oct 2012, 15:00 to 16:30
Venue:
A-212 (STCS Seminar Room)
(Scan to add to calendar)
Abstract:
We will see how multigrid ideas can be used to reduce the computational complexity (computational cost) of estimating an expected value arising from the solution of a stochastic differential equation using Monte Carlo path simulations. In the simplest case of a Lipschitz payoff and a Euler discretization, the computational cost to achieve an accuracy of O(e) is reduced from O(e^-3) to O(e^-2 * (log e)^2). A brief overview of related concepts will be provided before discussing the main details of the paper. (e = \epsilon)
*Reference: *Giles, M.B., Multilevel Monte Carlo Path Simulation, Operations Research, 2008.
| Speaker: | Ankush Agarwal |
| Organiser: | Gugan Thoppe |
| Date: | Friday, 5 Oct 2012, 15:00 to 16:30 |
| Venue: | A-212 (STCS Seminar Room) |
(Scan to add to calendar)
Abstract:
We will see how multigrid ideas can be used to reduce the computational complexity (computational cost) of estimating an expected value arising from the solution of a stochastic differential equation using Monte Carlo path simulations. In the simplest case of a Lipschitz payoff and a Euler discretization, the computational cost to achieve an accuracy of O(e) is reduced from O(e^-3) to O(e^-2 * (log e)^2). A brief overview of related concepts will be provided before discussing the main details of the paper. (e = \epsilon)
*Reference: *Giles, M.B., Multilevel Monte Carlo Path Simulation, Operations Research, 2008.
*Reference: *Giles, M.B., Multilevel Monte Carlo Path Simulation, Operations Research, 2008.