A portfolio stock selection model based on expected utility, entropy and variance

Autor: Irene Brito
Přispěvatelé: Universidade do Minho
Rok vydání: 2023
Předmět:
Zdroj: Expert Systems with Applications. 213:118896
ISSN: 0957-4174
Popis: In the context of investment decision-making, the selection of stocks is important for a successful construction of portfolios. In this paper the expected utility, entropy and variance (EU-EV) model is applied for stock selection, which can be used as preselection model for mean-variance portfolio optimization problems. Based on the EU-EV risk, stocks are ranked and the best ranked stocks with lower risk are selected in order to form subsets of stocks, which are then used to construct portfolios. The EU-EV model is applied to the PSI 20 index, to the Euro Stoxx 50 index and to the Nasdaq 100 index. Subsets of selected stocks are analysed and their portfolios' efficiencies are compared with those of the portfolios obtained from the whole set of stocks using the mean-variance model. The results reveal that the EU-EV model is an adequate stock selection model for building up efficient portfolios with a lower number of stocks.
The author thanks the reviewers for helpful comments. The author thanks support from FCT (“Fundação para a Ciência e a Tecnologia”) through the Projects UIDB/00013/2020 and UIDP/00013/2020.
Databáze: OpenAIRE
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