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

He, T.; Coolen, F.P.A.; Coolen-Maturi, T.

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.

Citation

He, T., Coolen, F., & 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. https://doi.org/10.1002/asmb.2668

• Journal Article Type: Article
• Acceptance Date: Jan 11, 2022
• Online Publication Date: Jan 31, 2022
• Publication Date: Jun 17, 2022
• Deposit Date: Jan 11, 2022
• Publicly Available Date: Jan 31, 2023
• Journal: Applied Stochastic Models in Business and Industry
• Print ISSN: 1524-1904
• Electronic ISSN: 1526-4025
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 38
• Issue: 3
• Pages: 422-440
• DOI: https://doi.org/10.1002/asmb.2668
• Public URL: https://durham-repository.worktribe.com/output/1218309