Ranking the determinants of financial performance using machine learning methods: an application to BIST energy companies

Hasan Hüseyin Yıldırım; Ömer Faruk Rençber; Cevriye Yüksel Yıldırım

doi:10.53391/mmnsa.1594426

EN

Ranking the determinants of financial performance using machine learning methods: an application to BIST energy companies

Abstract

Energy has been a key driver of change globally. As a developing country, Türkiye's increasing energy demand and consumption highlight the growing importance of efficient and sustainable energy management for its future. This study aims to determine the variables of the financial performance of 12 energy companies. Three different models are created with the return on assets, return on equity, and net profit margin as financial performance indicators of 12 firms. 12 financial ratios are used as input variables as determinants of financial performance. In the analysis, 37 quarterly data between 2014Q4-2023Q4 are used as the sample period. In machine learning, 17 different algorithms are considered in the selection of the appropriate model. The findings indicate that the Bagged Tree algorithm achieved successful outcomes for the ROA target variable, the Boosted Tree model demonstrated effective performance for the ROE model, and the Linear SVM algorithm yielded favorable results for the NPM model. According to the result obtained by the LIME method, Liquidity Ratio and Cash Ratio affect the ROA, ROE, and NPM models positively, while inventory turnover affects the models negatively.

Keywords

Machine learning, financial performance, BIST, energy firms

References

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Details

Primary Language

English

Subjects

Financial Mathematics, Applied Mathematics (Other)

Journal Section

Research Article

Authors

Hasan Hüseyin Yıldırım ^*
0000-0002-5840-8418
Türkiye

Ömer Faruk Rençber
0000-0001-8020-2750
Türkiye

Cevriye Yüksel Yıldırım
0000-0001-5048-6502
Türkiye

Publication Date

December 31, 2024

Submission Date

December 1, 2024

Acceptance Date

December 30, 2024

Published in Issue

Year 2024 Volume: 4 Number: 5-Special Issue: ICAME'24

DOI

https://doi.org/10.53391/mmnsa.1594426

IZ

https://izlik.org/JA38NW27UK

APA

Yıldırım, H. H., Rençber, Ö. F., & Yüksel Yıldırım, C. (2024). Ranking the determinants of financial performance using machine learning methods: an application to BIST energy companies. Mathematical Modelling and Numerical Simulation With Applications, 4(5-Special Issue: ICAME’24), 165-186. https://doi.org/10.53391/mmnsa.1594426

AMA

1.Yıldırım HH, Rençber ÖF, Yüksel Yıldırım C. Ranking the determinants of financial performance using machine learning methods: an application to BIST energy companies. MMNSA. 2024;4(5-Special Issue: ICAME’24):165-186. doi:10.53391/mmnsa.1594426

Chicago

Yıldırım, Hasan Hüseyin, Ömer Faruk Rençber, and Cevriye Yüksel Yıldırım. 2024. “Ranking the Determinants of Financial Performance Using Machine Learning Methods: An Application to BIST Energy Companies”. Mathematical Modelling and Numerical Simulation With Applications 4 (5-Special Issue: ICAME’24): 165-86. https://doi.org/10.53391/mmnsa.1594426.

EndNote

Yıldırım HH, Rençber ÖF, Yüksel Yıldırım C (December 1, 2024) Ranking the determinants of financial performance using machine learning methods: an application to BIST energy companies. Mathematical Modelling and Numerical Simulation with Applications 4 5-Special Issue: ICAME’24 165–186.

IEEE

[1]H. H. Yıldırım, Ö. F. Rençber, and C. Yüksel Yıldırım, “Ranking the determinants of financial performance using machine learning methods: an application to BIST energy companies”, MMNSA, vol. 4, no. 5-Special Issue: ICAME’24, pp. 165–186, Dec. 2024, doi: 10.53391/mmnsa.1594426.

ISNAD

Yıldırım, Hasan Hüseyin - Rençber, Ömer Faruk - Yüksel Yıldırım, Cevriye. “Ranking the Determinants of Financial Performance Using Machine Learning Methods: An Application to BIST Energy Companies”. Mathematical Modelling and Numerical Simulation with Applications 4/5-Special Issue: ICAME’24 (December 1, 2024): 165-186. https://doi.org/10.53391/mmnsa.1594426.

JAMA

1.Yıldırım HH, Rençber ÖF, Yüksel Yıldırım C. Ranking the determinants of financial performance using machine learning methods: an application to BIST energy companies. MMNSA. 2024;4:165–186.

MLA

Yıldırım, Hasan Hüseyin, et al. “Ranking the Determinants of Financial Performance Using Machine Learning Methods: An Application to BIST Energy Companies”. Mathematical Modelling and Numerical Simulation With Applications, vol. 4, no. 5-Special Issue: ICAME’24, Dec. 2024, pp. 165-86, doi:10.53391/mmnsa.1594426.

Vancouver

1.Hasan Hüseyin Yıldırım, Ömer Faruk Rençber, Cevriye Yüksel Yıldırım. Ranking the determinants of financial performance using machine learning methods: an application to BIST energy companies. MMNSA. 2024 Dec. 1;4(5-Special Issue: ICAME’24):165-86. doi:10.53391/mmnsa.1594426

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