A Markov Decision Process Model for Optimal Trade of Options Using Statistical Data

This paper presents a Markov decision process model for calculating optimal decision policy regarding the trade of options assuming the American options trading system. The proposed model incorporates the conditional probabilities of option prices given various features (or factors) that affect thos...

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Bibliographic Details
Published inComputational economics Vol. 58; no. 2; pp. 327 - 346
Main Authors Nasir, Ali, Khursheed, Ambreen, Ali, Kazim, Mustafa, Faisal
Format Journal Article
LanguageEnglish
Published New York Springer US 01.08.2021
Springer Nature B.V
Subjects
Behavioral/Experimental Economics
Computer Appl. in Social and Behavioral Sciences
Decision analysis
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Economics and Finance
Iterative methods
Markov analysis
Markov processes
Math Applications in Computer Science
Operations Research/Decision Theory
Options trading
Policy making
Prices
Sales
Securities prices
Trading
Markov chain
American options
Optimal policy
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Summary:This paper presents a Markov decision process model for calculating optimal decision policy regarding the trade of options assuming the American options trading system. The proposed model incorporates the conditional probabilities of option prices given various features (or factors) that affect those prices. The generation of such probabilities requires statistical data of the feature values as well as the option price values. Given the availability of statistical data, the paper explains how the Markov decision process model can be formulated and solved using ‘value iteration’ to calculate optimal decision policy that maximizes the accumulative return. The model has been applied to the data of Microsoft and Coca Cola options. Analysis in the case study reveals how optimal decision policy can be interpreted and used for making sales or purchase decisions regarding various options at hand. The results indicate that there are significant advantages for the financial community including, but not limited to the investors who utilize our proposed approach.
ISSN:0927-7099
1572-9974
DOI:10.1007/s10614-020-10030-4