Efficient option risk measurement with reduced model risk



Mitra, S
(2017) Efficient option risk measurement with reduced model risk. Insurance: Mathematics and Economics, 72. pp. 163-174.

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Abstract

Options require risk measurement that is also computationally efficient as it is important to derivatives risk management. There are currently few methods that are specifically adapted for efficient option risk measurement. Moreover, current methods rely on series approximations and incur significant model risks, which inhibit their applicability for risk management. In this paper we propose a new approach to computationally efficient option risk measurement, using the idea of a replicating portfolio and coherent risk measurement. We find our approach to option risk measurement provides fast computation by practically eliminating nonlinear computational operations. We reduce model risk by eliminating calibration and implementation risks by using mostly observable data, we remove internal model risk for complex option portfolios by not admitting arbitrage opportunities, we are also able to incorporate liquidity or model misspecification risks. Additionally, our method enables tractable and convex optimisation of portfolios containing multiple options. We conduct numerical experiments to test our new approach and they validate it over a range of option pricing parameters.

Item Type: Article
Additional Information: publisher: Elsevier articletitle: Efficient option risk measurement with reduced model risk journaltitle: Insurance: Mathematics and Economics articlelink: http://dx.doi.org/10.1016/j.insmatheco.2016.09.006 content_type: article copyright: Crown Copyright © 2016 Published by Elsevier B.V. All rights reserved.
Uncontrolled Keywords: option risk, model risk, risk measurement, liquidity risk, option trading strategies
Depositing User: Symplectic Admin
Date Deposited: 13 May 2019 12:54
Last Modified: 19 Jan 2023 00:53
DOI: 10.1016/j.insmatheco.2016.09.006
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3038209

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