Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/146973
Title: MULTILEVEL MONTE CARLO METHODS IN FINANCE.
Authors: GREGORY ANG TAI XIANG
Keywords: Multilevel Monte Carlo, Multilevel Particle Filter
Issue Date: 9-Apr-2018
Citation: GREGORY ANG TAI XIANG (2018-04-09). MULTILEVEL MONTE CARLO METHODS IN FINANCE.. ScholarBank@NUS Repository.
Abstract: This project brings the frontier of the Multilevel literature to the context of option pricing. A key element is the computation of complex high-dimensional integrals when evaluating the expected payoff. Such integrals often do not have closed form solutions, hence requiring numerical evaluation. We adopt novel Monte Carlo methods to estimate these integrals. We examine the reduction in variance by comparing the ordinary Monte Carlo (MC) Method against Multilevel Monte Carlo (MLMC). MLMC is implemented by sampling coupled discretised di usion processes. The variance of the MLMC estimate is given by O( T ) where T is the time to maturity and is some constant greater than 1. To reduce the variance to O(T), we employ Particle Filters and the Multilevel Particle Filter (MLPF). We then explore using Transport Maps to approximate our target distribution, which we postulate has a variance of O(T). Finally, we evaluate the methods on the S&P500 index.
URI: http://scholarbank.nus.edu.sg/handle/10635/146973
Appears in Collections:Bachelor's Theses (Restricted)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
Gregory Ang Tai Xiang AY1718 Sem 2.pdf5.08 MBAdobe PDF

RESTRICTED

NoneLog In

Page view(s)

2
checked on Sep 13, 2018

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.