Asset Allocation through Grey Wolf Optimization: A Case of KSE-30 Index

Authors

  • Javed Iqbal Bahauddin Zakariya University, Multan, Pakistan.
  • Abid Mehmood Karachi Institute of Economics & Technology (KIET), Karachi, Pakistan.
  • Aboubakar Mirza Bahauddin Zakariya University, Multan, Pakistan.
  • Abdul Khaliq Bahauddin Zakariya University, Multan, Pakistan.

DOI:

https://doi.org/10.52131/pjhss.2023.1101.0383

Keywords:

Market Capitalization , Asset Allocation , Grey Wolf Optimization , KSE-30 Index

Abstract

This article is an effort to aid investors by drawing attention to select investment items. Grey Wolf Optimization (GWO), TOPSIS with Eigenvector, Market Capitalization, and the Equal Weighted Technique are the four main methods discussed in this paper. This study uses the KSE-30 Index as its sample size; however, because to a lack of data, only 26 businesses are chosen for analysis using 10 criteria. All four methods are implemented and weights are determined based on these criteria. These weights are then utilized in conjunction with MATLAB's in-built tools to construct a portfolio. Based on its ability to generate the greatest possible portfolio, GWO appears to be a powerful resource for affluent investors. Equal-weighted portfolios performed the worst, followed by the Eigenvector-TOPSIS technique, then Market Capitalization.

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Author Biographies

Javed Iqbal, Bahauddin Zakariya University, Multan, Pakistan.

Assistant Professor, Institute of Management Sciences

Abid Mehmood, Karachi Institute of Economics & Technology (KIET), Karachi, Pakistan.

College of Management Sciences (CoMS)

Aboubakar Mirza, Bahauddin Zakariya University, Multan, Pakistan.

Assistant Professor, School of Economics

Abdul Khaliq, Bahauddin Zakariya University, Multan, Pakistan.

MS Scholar, Institute of Management Sciences

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Published

2023-03-31

How to Cite

Iqbal, J., Mehmood, A. ., Mirza, A. ., & Khaliq, A. . (2023). Asset Allocation through Grey Wolf Optimization: A Case of KSE-30 Index. Pakistan Journal of Humanities and Social Sciences, 11(1), 670–681. https://doi.org/10.52131/pjhss.2023.1101.0383

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