COMPARISON OF MEAN-VARIANCE MODEL AND FIREFLY ALGORITHM PERFORMANCE: BIST 30 INDEX APPLICATION

Authors : Diler Türkoğlu

Pages : 470-486

Doi:10.14514/beykozad.1579573

View : 39 | Download : 127

Publication Date : 2025-12-17

Article Type : Research Paper

Abstract :Market participants manage their portfolios with the goal of maximizing profits and avoiding risk, and portfolio optimization is crucial to this process. By quantifying risk, Markowitz\\\'s mean-variance model (1952) opened up new avenues for portfolio optimization. However, in the last several years, advances in finance and many other fields have been illuminated by artificial intelligence algorithms. In order to evaluate the effectiveness of the Firefly algorithm with Markowitz\\\'s mean-variance model, this research will focus on optimization issues, as this method is one of the ways to solve difficulties. The performance metrics of the portfolios, which include expected return, risk, sharpe ratio, coefficient of variation, and downside risk, were determined using data from the companies listed in the BIST30 Index between January 1, 2018, and December 31, 2023, in accordance with the conventional mean variance model. The performance of the two models was then compared when the metrics in issue were recalculated using the Firefly algorithm, a Meta-Heuristic artificial intelligence technique, taking into account the data from 2023, when the most successful results were attained. The analysis\\\'s high sharpe ratio and expected return demonstrate that the firefly algorithm outperforms the mean-variance model; however, when assessing the findings, it\\\'s important to keep in mind that, given the constraints on risk management, the firefly algorithm may have certain drawbacks due to the higher downside risk it detected than the mean-variance model.
Keywords : Portföy Optimizasyonu, Ortalama Varyans, Ateş Böceği Algoritması.

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