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Pricing exotic options in the incomplete market: an imprecise probability method

He, T. and Coolen, F.P.A. and Coolen-Maturi, T. (2022) 'Pricing exotic options in the incomplete market: an imprecise probability method.', Applied Stochastic Models in Business and Industry, 38 (3). pp. 422-440.

Abstract

This paper considers a novel exotic option pricing method for incomplete markets. Nonparametric Predictive Inference (NPI) is applied to the option pricing procedure based on the binomial tree model allowing the method to evaluate exotic options with limited information and few assumptions. As the implementation of the NPI method is greatly simplified by the monotonicity of the option payoff in the tree, we categorize exotic options by their payoff monotonicity and study a typical type of exotic option in each category, the barrier option and the look-back option. By comparison with the classic binomial tree model, we investigate the performance of our method either with different moneyness or varying maturity. All outcomes show that our model offers a feasible approach to price the exotic options with limited information, which makes it can be utilized for both complete and incomplete markets.

Item Type:Article
Full text:Publisher-imposed embargo until 31 January 2023.
(AM) Accepted Manuscript
File format - PDF
(501Kb)
Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1002/asmb.2668
Publisher statement:This is the peer reviewed version of the following article: He, T., Coolen, F.P.A. & Coolen-Maturi, T. (2022). Pricing exotic options in the incomplete market: an imprecise probability method. Applied Stochastic Models in Business and Industry 38(3): 422-440, which has been published in final form at https://doi.org/10.1002/asmb.2668. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.
Date accepted:11 January 2022
Date deposited:11 January 2022
Date of first online publication:31 January 2022
Date first made open access:31 January 2023

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