EconPapers    
Economics at your fingertips  
 

Variance reduction for Monte Carlo simulation in a stochastic volatility environment

Jean-Pierre Fouque and Tracey Andrew Tullie

Quantitative Finance, 2002, vol. 2, issue 1, 24-30

Abstract: We propose a variance reduction method for Monte Carlo computation of option prices in the context of stochastic volatility. This method is based on importance sampling using an approximation of the option price obtained by a fast mean-reversion expansion introduced in Fouque et al (2000 Derivatives in Financial Markets with Stochastic Volatility (Cambridge: Cambridge University Press)). We compare this with the small noise expansion method proposed in Fournie et al (1997 Asymptotic Anal. 14 361-76) and demonstrate numerically the efficiency of our method, in particular in the presence of a skew.

Date: 2002
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1088/1469-7688/2/1/302 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:quantf:v:2:y:2002:i:1:p:24-30

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RQUF20

DOI: 10.1088/1469-7688/2/1/302

Access Statistics for this article

Quantitative Finance is currently edited by Michael Dempster and Jim Gatheral

More articles in Quantitative Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:quantf:v:2:y:2002:i:1:p:24-30