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Modelling stock selection using ordered weighted averaging operator
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DOI：10.1002/int.22029.png)
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Abstract
En 中文
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.
Keywords:
linear programming
ordered weighted averaging
preference voting
stock selection
Tehran stock market
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