DocumentCode :
3000739
Title :
Function-approximation-based Perfect Control Variates for Pricing American Options
Author :
Bolia, Nomesh ; Juneja, Sandeep
Author_Institution :
Tata Inst. of Fundamental Res., Mumbai
fYear :
2005
fDate :
4-4 Dec. 2005
Firstpage :
1876
Lastpage :
1883
Abstract :
Monte Carlo simulation techniques that use function approximations have been successfully applied to approximately price multidimensional American options. However, for many pricing problems the time required to get accurate estimates can still be prohibitive, and this motivates the development of variance reduction techniques. In this paper, we describe a zero variance or ´perfect´ control variate to price American options. We then discuss how function approximation may be used to approximate this perfect control variate. Empirically, we observe that on simple one dimensional examples, this approximately perfect control variate gives orders of magnitude of variance reduction compared to naive estimation
Keywords :
function approximation; pricing; American option pricing; Monte Carlo simulation; function approximation; multidimensional price approximation; perfect control variate; variance reduction technique; zero variance; Continuous time systems; Function approximation; Induction generators; Monte Carlo methods; Optimal control; Pricing; State estimation; Upper bound;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference, 2005 Proceedings of the Winter
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-9519-0
Type :
conf
DOI :
10.1109/WSC.2005.1574464
Filename :
1574464
Link To Document :
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