Estimating risks of option books using neural-SDE market models

35 Pages Posted: 16 Feb 2022

See all articles by Samuel N. Cohen

Samuel N. Cohen

University of Oxford - Mathematical Institute; The Alan Turing Institute

Christoph Reisinger

University of Oxford - Mathematical Institute; University of Oxford - Oxford-Man Institute of Quantitative Finance

Sheng Wang

University of Oxford - Mathematical Institute

Date Written: February 15, 2022

Abstract

In this paper, we examine the capacity of an arbitrage-free neural-SDE market model to produce realistic scenarios for the joint dynamics of multiple European options on a single underlying. We subsequently demonstrate its use as a risk simulation engine for option portfolios. Through backtesting analysis, we show that our models are more computationally efficient and accurate for evaluating the Value-at-Risk (VaR) of option portfolios, with better coverage performance and less procyclicality than standard filtered historical simulation approaches.

Keywords: Market models, European options; risk measures, market simulators; no-arbitrage, neural SDE

JEL Classification: C14, C45, C51

Suggested Citation

Cohen, Samuel N. and Reisinger, Christoph and Reisinger, Christoph and Wang, Sheng, Estimating risks of option books using neural-SDE market models (February 15, 2022). Available at SSRN: https://ssrn.com/abstract=4035044 or http://dx.doi.org/10.2139/ssrn.4035044

Samuel N. Cohen

University of Oxford - Mathematical Institute ( email )

Woodstock Road
Oxford, Oxfordshire OX26GG
United Kingdom

The Alan Turing Institute ( email )

British Library
96 Euston Road
London, NW1 2DB
United Kingdom

Christoph Reisinger

University of Oxford - Mathematical Institute ( email )

Radcliffe Observatory, Andrew Wiles Building
Woodstock Rd
Oxford, Oxfordshire OX2 6GG
United Kingdom

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

Eagle House
Walton Well Road
Oxford, Oxfordshire OX2 6ED
United Kingdom

Sheng Wang (Contact Author)

University of Oxford - Mathematical Institute ( email )

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
61
Abstract Views
160
rank
486,559
PlumX Metrics