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Entropy 2017, 19(10), 508; https://doi.org/10.3390/e19100508

Stock Selection for Portfolios Using Expected Utility-Entropy Decision Model

School of Economics and Management, Beihang University, Beijing 100083, China
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Received: 8 June 2017 / Revised: 16 August 2017 / Accepted: 19 September 2017 / Published: 21 September 2017
(This article belongs to the Section Information Theory)
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Abstract

Yang and Qiu proposed and then recently improved an expected utility-entropy (EU-E) measure of risk and decision model. When segregation holds, Luce et al. derived an expected utility term, plus a constant multiplies the Shannon entropy as the representation of risky choices, further demonstrating the reasonability of the EU-E decision model. In this paper, we apply the EU-E decision model to selecting the set of stocks to be included in the portfolios. We first select 7 and 10 stocks from the 30 component stocks of Dow Jones Industrial Average index, and then derive and compare the efficient portfolios in the mean-variance framework. The conclusions imply that efficient portfolios composed of 7(10) stocks selected using the EU-E model with intermediate intervals of the tradeoff coefficients are more efficient than that composed of the sets of stocks selected using the expected utility model. Furthermore, the efficient portfolio of 7(10) stocks selected by the EU-E decision model have almost the same efficient frontier as that of the sample of all stocks. This suggests the necessity of incorporating both the expected utility and Shannon entropy together when taking risky decisions, further demonstrating the importance of Shannon entropy as the measure of uncertainty, as well as the applicability of the EU-E model as a decision-making model. View Full-Text
Keywords: Shannon entropy; portfolio; investment; stock selection; EU-E decision model Shannon entropy; portfolio; investment; stock selection; EU-E decision model
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Yang, J.; Feng, Y.; Qiu, W. Stock Selection for Portfolios Using Expected Utility-Entropy Decision Model. Entropy 2017, 19, 508.

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