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Abstract

Enhancing Investment Decision-Making in the Investment Portfolio of Iraqi Banks Using Genetic Algorithms: A Smart Approach for the Period 2018–2023

Noor Sabah Hameed Al-Dahaan

Ph.D in Financial Management, Associate Professor of the Department of Finance and Banking Sciences. University of Kerbala, Iraq

Noor Salah Alramadan

Ph.D in Banking Management, Associate Professor of the Department of Finance and Banking Sciences. University of Kerbala, Iraq

87-101 Vol: 16, Issue: 1, 2026
Receiving Date: 2025-12-05
Acceptance Date: 2026-01-23
Publication Date: 2026-02-19
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http://doi.org/10.37648/ijtbm.v16i01.006

Abstract

The study examines the use of Genetic Algorithms (GAs) in optimizing investment portfolio decisions at Iraqi banks between 2018 and 2023. Even the traditional portfolio models, e.g., Mean-Variance theory, CAPM, etc., do not flow very well into a volatile, constraint-dominant marketplace that is the Iraqi market. This research would utilize the evolutionary principles of GAs to maximize returns generated and reduce investment-related risk in banks like Islamic Iraqi, Commercial Iraqi, Middle East, Iraqi Investment, Baghdad, Iraqi Credit etc. The work bases the revision of the index and asset weighting by GA on the historical financial data and compares the performance of portfolios using GA and the traditional ones. Its indication shows that though the GA portfolios are a weak contribution statistically, they do dramatically better than the conventional methods in the practical sense. The results of the research provide support to the idea that GAs could better investment efficiency within the emerging economies and point to the necessity of technological innovation in the field of finance in Iraq.

Keywords: Genetic Algorithms (GAs); Risk-Return Tradeoff; Treynor Ratio; Mean-Variance Model; Metaheuristic Algorithms; Portfolio Performance; Artificial Intelligence in Finance; Risk Management.

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