Exploring Nonparametric Strategies for Pricing American Index Options

HYEONGMIN, BYUN and HYUNWOONG, JI and JAEWOOK, LEE and YOUNGDOO, SON (2015) Exploring Nonparametric Strategies for Pricing American Index Options. In: International Conference on Advances in Economics, Social Science and Human Behaviour Study - ESSHBS 2015, 21 - 22 February 2015, Hotel Lebua at State Tower.

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Abstract

Nonparametric models such as machine learning methods that are counterparts of parametric financial models were applied to pricing American index options. 10 year S&P 100 Index American options were adopted as experimental dataset and the both training (in-sample) and test (out-of-sample) errors of machine learning and ad-hoc pricing which is a conventional financial pricing model were calculated and compared to each other. We found out that Bayesian neural network outperforms the other pricing methods. Furthermore, we suggested an ensemble method which takes advantage of both machine learning method and ad-hoc pricing method and as a consequence, it shows the best performance.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: American Option, Option Pricing, Machine Learning, Ad-hoc Pricing.
Depositing User: Mr. John Steve
Date Deposited: 09 May 2019 11:02
Last Modified: 09 May 2019 11:02
URI: http://publications.theired.org/id/eprint/2050

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