Stacked Monte Carlo for Option Pricing

12 Pages Posted: 23 Apr 2019

See all articles by Antoine (Jack) Jacquier

Antoine (Jack) Jacquier

Imperial College London; The Alan Turing Institute

Emma Malone

Lloyds Banking Group

Mugad Oumgari

Lloyds Banking Group

Date Written: March 26, 2019

Abstract

We introduce a stacking version of the Monte Carlo algorithm in the context of option pricing. Introduced recently for aeronautic computations, this simple technique, in the spirit of current machine learning ideas, learns control variates by approximating Monte Carlo draws with some specified function. We describe the method from first principles and suggest appropriate fits, and show its efficiency to evaluate European and Asian Call options in constant and stochastic volatility models.

Keywords: option pricing, machine learning, Monte Carlo, stochastic volatility

Suggested Citation

Jacquier, Antoine and Malone, Emma and Oumgari, Mugad, Stacked Monte Carlo for Option Pricing (March 26, 2019). Available at SSRN: https://ssrn.com/abstract=3360332 or http://dx.doi.org/10.2139/ssrn.3360332

Antoine Jacquier (Contact Author)

Imperial College London ( email )

South Kensington Campus
London SW7 2AZ, SW7 2AZ
United Kingdom

HOME PAGE: http://wwwf.imperial.ac.uk/~ajacquie/

The Alan Turing Institute ( email )

British Library, 96 Euston Road
London, NW12DB
United Kingdom

Emma Malone

Lloyds Banking Group ( email )

10 Gresham Street
London, EC2V 7AE
United Kingdom

Mugad Oumgari

Lloyds Banking Group ( email )

10 Gresham Street
London, EC2V 7AE
United Kingdom

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