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BWM—RAPS Approach for Evaluating and Ranking Banking Sector Companies Based on Their Financial Indicators in the Saudi Stock Market

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  • Mohammed H. Alamoudi

    (Department of Industrial Engineering, College of Engineering, King Abdulaziz University, Jeddah 80204, Saudi Arabia)

  • Omer A. Bafail

    (Department of Industrial Engineering, College of Engineering, King Abdulaziz University, Jeddah 80204, Saudi Arabia)

Abstract

Seeking the greatest possible return on long-term investments, investors naturally seek equities of the best-performing companies that fit their investment timeframe. Long-term investment success rests on selecting the best companies, which requires a challenging analysis reviewing voluminous and often-conflicting data about companies and understanding broader economic forecasts. This paper undertook a case study deployment of MCDM methodologies to examine the suitability and effectiveness of Multi-Criteria Decision-Making (MCDM) methods in assessing and ranking the best stocks for portfolio inclusion. A combination of MCDM techniques comprised a methodology to evaluate and rank Saudi Arabian banking stocks based on their performance in the Saudi stock market. Specifically, the paper combined the Best–Worst Method (BWM) and Ranking Alternatives by Perimeter Similarity (RAPS) for the analysis. BWM calculated each criterion’s relative impact (weight) in selecting a stock. RAPS then used the weighting to rank the results of the investigation. The study’s findings yielded encouraging results regarding using an integrated MCDM technique to derive optimal banking sector securities in the expansive Saudi stock market. The novel application of the robust RAPS technique combined with BWM encourages continued and increased use of MCDM techniques in financial matters and broader application in evaluating equities.

Suggested Citation

  • Mohammed H. Alamoudi & Omer A. Bafail, 2022. "BWM—RAPS Approach for Evaluating and Ranking Banking Sector Companies Based on Their Financial Indicators in the Saudi Stock Market," JRFM, MDPI, vol. 15(10), pages 1-20, October.
    • Handle: RePEc:gam:jjrfmx:v:15:y:2022:i:10:p:467-:d:944561
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    2. Gao, Peng & Yang, Yang & Li, Fei & Ge, Jiaxin & Yin, Qianqian & Wang, Ruikun, 2024. "Research on integrated decision making of multiple load combination forecasting for integrated energy system," Energy, Elsevier, vol. 311(C).

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