Pricing and Risk Management with Stochastic Volatility Using Importance Sampling

31 Pages Posted: 30 Oct 2012 Last revised: 20 Mar 2014

See all articles by Przemyslaw Stan Stilger

Przemyslaw Stan Stilger

University of Manchester - Manchester Business School

Simon Acomb

Acomb Financial Research Limited

Ser-Huang Poon

Alliance Manchester Business School, University of Manchester; Alan Turing Institute

Date Written: March 20, 2014

Abstract

Abstract In this paper, we apply importance sampling to Heston's stochastic volatility model and Bates's stochastic volatility model with jumps. We propose an effective numerical scheme that dramatically improves the speed of importance sampling. We show how the Greeks can be computed using the Likelihood Ratio Method based on characteristic function, and how combining it with importance sampling leads to a significant variance reduction for the Greeks. All results are illustrated using European and barrier options.

Keywords: Importance sampling, Simulation, Stochastic volatility

Suggested Citation

Stilger, Przemyslaw Stan and Acomb, Simon and Poon, Ser-Huang, Pricing and Risk Management with Stochastic Volatility Using Importance Sampling (March 20, 2014). Available at SSRN: https://ssrn.com/abstract=2168415 or http://dx.doi.org/10.2139/ssrn.2168415

Przemyslaw Stan Stilger (Contact Author)

University of Manchester - Manchester Business School ( email )

Booth Street West
Manchester, M15 6PB
United Kingdom

Simon Acomb

Acomb Financial Research Limited ( email )

Carnforth, Lancashire, LA6 1AZ
United Kingdom

Ser-Huang Poon

Alliance Manchester Business School, University of Manchester ( email )

Alliance Manchester Business School
Booth Street West
Manchester, Manchester M15 6PB
United Kingdom
+44 161 275 4031 (Phone)
+44 161 275 4023 (Fax)

HOME PAGE: http://www.manchester.ac.uk/research/Ser-huang.poon/

Alan Turing Institute ( email )

British Library, 96 Euston Road
96 Euston Road
London, NW12DB
United Kingdom

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