A Three-Phase Algorithm for Selecting Optimal Investment Options Based on Financial Ratios of Stock Companies

Journal Title: Journal of Operational and Strategic Analytics - Year 2024, Vol 2, Issue 4

Abstract

The identification of optimal stock or portfolio options is a critical concern for investors aiming to maximize profitability within financial markets. With the increasing complexity of available alternatives and the growing volume of financial data, selecting the most suitable investment has become more challenging. Decision-makers often face difficulties in navigating these vast data sets and require robust support tools to simplify and enhance the decision-making process. This study proposes a three-phase approach designed to reduce data complexity and facilitate more detailed analysis. In the initial phase, firms demonstrating low operational efficiency, as indicated by their inventory turnover ratio, were excluded from further consideration. In the subsequent phase, data envelopment analysis (DEA) was employed to assess the efficiency of remaining firms, with those exhibiting efficiency scores lower than one being removed from further investigation. Finally, the third phase involved determining the relative importance of each financial ratio through the calculation of their respective weights, allowing for the ranking of firms based on these adjusted values. The results of this approach provide decision-makers with a refined list of viable investment options, contributing to more informed stock portfolio optimization decisions.

Authors and Affiliations

Zahra Joorbonyan, Sapan Kumar Das, Seyed Ali Noorkhah, Ali Sorourkhah

Keywords

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  • EP ID EP753406
  • DOI https://doi.org/10.56578/josa020401
  • Views 11
  • Downloads 1

How To Cite

Zahra Joorbonyan, Sapan Kumar Das, Seyed Ali Noorkhah, Ali Sorourkhah (2024). A Three-Phase Algorithm for Selecting Optimal Investment Options Based on Financial Ratios of Stock Companies. Journal of Operational and Strategic Analytics, 2(4), -. https://europub.co.uk/articles/-A-753406