Pricing Window Barrier Options with a Hybrid Stochastic-Local Volatility Model

2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics

8 Pages Posted: 20 Nov 2013 Last revised: 23 Feb 2014

See all articles by Yu Tian

Yu Tian

Monash University

Zili Zhu

Government of the Commonwealth of Australia - CSIRO (Commonwealth Scientific and Industrial Research Organisation)

Geoffrey Lee

Government of the Commonwealth of Australia - CSIRO (Commonwealth Scientific and Industrial Research Organisation)

Thomas Lo

Government of the Commonwealth of Australia - CSIRO (Commonwealth Scientific and Industrial Research Organisation)

Fima Klebaner

Monash University

Kais Hamza

Monash University

Date Written: February 7, 2014

Abstract

In this paper, we present our research on pricing window barrier options under a hybrid stochastic-local volatility (SLV) model in the foreign exchange (FX) market. Due to the hybrid effect of the local volatility and stochastic volatility components of the model, the SLV model can reproduce the market implied volatility surface, and can improve the pricing accuracy for exotic options at the same time. In this paper, numerical techniques such as Monte Carlo and finite difference methods for standard exotic barrier options under the SLV model are extended to pricing window barrier options and numerical results produced by the SLV model are used to examine the performance and accuracy of the model for pricing window barrier options.

Keywords: stochastic-local volatility, leverage function, window barrier, Monte Carlo, finite difference

JEL Classification: C6, D4, G12

Suggested Citation

Tian, Yu and Zhu, Zili and Lee, Geoffrey and Lo, Thomas and Klebaner, Fima and Hamza, Kais, Pricing Window Barrier Options with a Hybrid Stochastic-Local Volatility Model (February 7, 2014). 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics, Available at SSRN: https://ssrn.com/abstract=2356816 or http://dx.doi.org/10.2139/ssrn.2356816

Yu Tian (Contact Author)

Monash University ( email )

Melbourne, Victoria VIC 3800
Australia

Zili Zhu

Government of the Commonwealth of Australia - CSIRO (Commonwealth Scientific and Industrial Research Organisation) ( email )

Gate 5 Normanby Road
Clayton
Melbourne, Australian Capital Territory 3168
Australia
61 3 95458003 (Phone)
61 3 9545 8080 (Fax)

Geoffrey Lee

Government of the Commonwealth of Australia - CSIRO (Commonwealth Scientific and Industrial Research Organisation) ( email )

41 Boggo Rd
Dutton Park, Queensland
Australia

Thomas Lo

Government of the Commonwealth of Australia - CSIRO (Commonwealth Scientific and Industrial Research Organisation) ( email )

41 Boggo Rd
Dutton Park, Queensland
Australia

Fima Klebaner

Monash University ( email )

23 Innovation Walk
Wellington Road
Clayton, Victoria 3800
Australia

Kais Hamza

Monash University ( email )

23 Innovation Walk
Wellington Road
Clayton, Victoria 3800
Australia

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