Modelling stock selection using ordered weighted averaging operator |
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| Authors: | Mohaddeseh Hajjami Gholam R Amin |
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| Affiliation: | 1. Saint John College, University of New Brunswick at Saint John, Saint John, NB, Canada;2. Faculty of Business, University of New Brunswick at Saint John, Saint John, NB, Canada |
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| Abstract: | The main objective of stock selection is to select a set of assets in the stock market with high‐expected returns. There are many financial variables that affect the performance of stock firms. This paper proposes a novel linear programming model based on the ordered weighted averaging (OWA) operator for identifying superior stocks without requiring the re‐ordering process. The paper first converts a stock selection problem into a preference voting system by considering two different perspectives: an investor perspective in which the goal is to select stocks with the highest return, and a creditor perspective in which the goal is to maximize the repayment ability. The OWA operator is then used to formulate a linear programming model for identifying superior stocks. The usefulness of the proposed method in this paper is shown through an application in the Tehran stock market. |
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| Keywords: | linear programming ordered weighted averaging preference voting stock selection Tehran stock market |
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