<abstract xmlns="http://www.w3.org/1999/xhtml">

<bold>Aim/purpose</bold> – The aim of the paper is to rank the optimal portfolios of shares of companies listed on the Warsaw Stock Exchange, taking into account the investor’s propensity to risk.
<bold>Design/methodology/approach</bold> – Investment portfolios consisting of varied number of companies selected from WIG 20 index were built. Next, the weights of equity holdings of these companies in the entire portfolio were determined, maximizing portfolio’s expected (square) utility function, and then the obtained structures were compared between investors with various levels of risk propensity. Using Hellwig’s taxonomic development measure, a ranking of optimum stock portfolios depending on the investor’s risk propensity was prepared. The research analyzed quotations from 248 trading sessions.
<bold>Findings</bold> – The findings indicated that whilst there are differences in the weight structures of equity holdings in the entire portfolio between the investor characterized by aversion to risk at the level of γ = 10 and the investor characterized by aversion to risk at the level of γ = 100, the rankings of the constructed optimum portfolios demonstrate strong similarity. The study validated, in conformity with the literature, that with the increase in the number of equity holdings in the portfolio, the portfolio risk initially decreases and then becomes stable at a certain level.
<bold>Research implications/limitations</bold> – The study used data from the past as for which there is no guarantee that they will be adequate for the future. There is sensitivity to the selection of the period from which the historic data come. When changing the period of the analyzed historic data by a small time unit it may prove that the portfolio composition will become totally different.
<bold>Originality/value/contribution</bold> – The paper compares the composition of optimum stock portfolios depending on the investor’s propensity to risk. Their ranking was created using the taxonomic method for this purpose. Taking advantage of this method also additional variables can be taken into account, which describe and differentiate the portfolio and they can be assigned relevant significance depending on the investor’s preferences.
</abstract>

Aim/purpose – The aim of the paper is to rank the optimal portfolios of shares of companies listed on the Warsaw Stock Exchange, taking into account the investor’s propensity to risk.
Design/methodology/approach – Investment portfolios consisting of varied number of companies selected from WIG 20 index were built. Next, the weights of equity holdings of these companies in the entire portfolio were determined, maximizing portfolio’s expected (square) utility function, and then the obtained structures were compared between investors with various levels of risk propensity. Using Hellwig’s taxonomic development measure, a ranking of optimum stock portfolios depending on the investor’s risk propensity was prepared. The research analyzed quotations from 248 trading sessions.
Findings – The findings indicated that whilst there are differences in the weight structures of equity holdings in the entire portfolio between the investor characterized by aversion to risk at the level of γ = 10 and the investor characterized by aversion to risk at the level of γ = 100, the rankings of the constructed optimum portfolios demonstrate strong similarity. The study validated, in conformity with the literature, that with the increase in the number of equity holdings in the portfolio, the portfolio risk initially decreases and then becomes stable at a certain level.
Research implications/limitations – The study used data from the past as for which there is no guarantee that they will be adequate for the future. There is sensitivity to the selection of the period from which the historic data come. When changing the period of the analyzed historic data by a small time unit it may prove that the portfolio composition will become totally different.
Originality/value/contribution – The paper compares the composition of optimum stock portfolios depending on the investor’s propensity to risk. Their ranking was created using the taxonomic method for this purpose. Taking advantage of this method also additional variables can be taken into account, which describe and differentiate the portfolio and they can be assigned relevant significance depending on the investor’s preferences.

Ranking of optimal stock portfolios determined on the basis of expected utility maximization criterion

Journal of Economics and Management

This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.

Aim/purpose – The aim of the paper is to rank the optimal portfolios of shares of companies listed on the Warsaw Stock Exchange, taking into account the...

Ranking of optimal stock portfolios determined on the basis of expected utility maximization criterion

Online veröffentlicht: 20. Mai 2021

Seitenbereich: 154 - 178

Eingereicht: 13. Okt. 2020

Akzeptiert: 31. März 2021

DOI: https://doi.org/10.22367/jem.2021.43.08

Schlüsselwörter
optimal portfolio, expected rate of return on the portfolio, portfolio standard deviation, expected utility theory, multidimensional comparative analysis

© 2021 Dawid Giemza, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.

Ranking of optimal stock portfolios determined on the basis of expected utility maximization criterion

Online veröffentlicht: 20. Mai 2021

Seitenbereich: 154 - 178

Eingereicht: 13. Okt. 2020

Akzeptiert: 31. März 2021

DOI: https://doi.org/10.22367/jem.2021.43.08

Schlüsselwörteroptimal portfolio, expected rate of return on the portfolio, portfolio standard deviation, expected utility theory, multidimensional comparative analysis

© 2021 Dawid Giemza, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.

Schlüsselwörter
optimal portfolio, expected rate of return on the portfolio, portfolio standard deviation, expected utility theory, multidimensional comparative analysis