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Game Theory and Stock Investment

Name: Game Theory and Stock Investment
Creator: Mahboob Ullah, Ghulam Rasool Lakhan, Amanullah Channa, Shabnam Gul
Keywords: 0502 economics and business, 05 social sciences, Game Theory, Loss-aversion, Stress, Stock's Investment.

descriptionPublicationkeyboard_double_arrow_right Article 04 Jun 2021Publisher:Zenodo

Authors: Mahboob Ullah, Ghulam Rasool Lakhan, Amanullah Channa, Shabnam Gul;

doi: 10.5281/zenodo.4900015 , 10.5281/zenodo.4900016

Game Theory and Stock Investment

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Abstract

The aim of this study is to provide an understanding regarding the investor’s situation of loss-aversion and stress during investment decisions in stock market, and the use of various mathematical models (game theories) to eliminate those situations. The objectives of this study are to know about the irrationalities in investor’s behavior in stock market, due to stress and loss-averse behavior of investors, and find-out the ways to deal with these behaviors. Qualitative research style used to gather data from the participants of the study. Semi-structured interviews designed to know about the experience and thoughts of each respondent in detail. A sample of 16 experienced stock marketers from Pakistan and USA selected for this study. The study found the specific kind of tensed and biased investor’s behaviors in the market, and found their solutions. This study obviously highpoints the ways to deal with stress and loss-averse behavior through mathematical analysis and some other suggestions.

Keywords

Game Theory, Loss-aversion, Stress, Stock's Investment.

3 Research products, page 1 of 1

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	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
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	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average