Cost Drivers and Financial Algorithm in the Nigerian Capital Market

Olufemi Akinloye Oyedare

doi:10.59413/eafj/v5.i2.4

Authors

Olufemi Akinloye Oyedare Accounting and Finance Department , Ajayi Crowther University Author

DOI:

https://doi.org/10.59413/eafj/v5.i2.4

Keywords:

Cost Drivers, Financial Algorithm, Capital Market, Nigeria, Market Efficiency

Abstract

This study examines the interaction between cost drivers and financial algorithms in shaping capital market outcomes in Nigeria. Using a balanced panel dataset of fifteen listed deposit money banks over the period 2018–2023, the study employs panel econometric techniques, including fixed effects, random effects, and Hausman specification tests. Findings reveal that operating and financing costs exert significant negative effects on market performance, while strategic expenditure and financial algorithms positively influence valuation efficiency and investor responsiveness. The Hausman test confirms the suitability of the fixed effects model, indicating the presence of firm-specific heterogeneity. The study concludes that effective cost management combined with algorithmic financial integration enhances capital market efficiency in Nigeria. Policy implications emphasize improved cost control, increased digital investment, and strengthened regulatory frameworks to support algorithmic trading systems.

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References

Adesina, K. T., & Tiamiyu, A. O. (2025). Empirical analysis of cost management and profitability of manufacturing companies in Nigeria. International Journal of Financial Studies, 13(1), 44–61.

Aguiar, M., & Gopinath, G. (2007). Emerging market business cycles: The cycle is the trend. Journal of political Economy, 115(1), 69-102. DOI: https://doi.org/10.1086/511283

Agarwal, M. (2024). Global Financial Stability Report 2024: Times of Uncertainty, Artificial Intelligence, and Financial Stability1. Finance India, 38(4), 867-870.

Bello, H. O., Ige, A. B., & Ameyaw, M. N. (2024). Deep learning in high-frequency trading: conceptual challenges and solutions for real-time fraud detection. World Journal of Advanced Engineering Technology and Sciences, 12(02), 035-046. DOI: https://doi.org/10.30574/wjaets.2024.12.2.0265

Boukherouaa, E., Shabsigh, G., & Al Ajmi, J. (2021). Fintech in capital markets: Opportunities and risks. International Monetary Fund Working Paper.

Cortesi, A., & Vena, L. (2019). Disclosure quality under Integrated Reporting: A value relevance approach. Journal of cleaner production, 220, 745-755. DOI: https://doi.org/10.1016/j.jclepro.2019.02.155

Dakalbab, F. (2024). Artificial intelligence techniques in financial trading: A systematic literature review. Journal of King Saud University – Computer and Information Sciences, 36(2), 102015. DOI: https://doi.org/10.1016/j.jksuci.2024.102015

Dou, W. W., Goldstein, I., & Ji, Y. (2025). Ai-powered trading, algorithmic collusion, and price efficiency (No. w34054). National Bureau of Economic Research. DOI: https://doi.org/10.3386/w34054

El Alami, S. E., Mouiha, A., Hafid, A., & Alaoui, A. E. H. (2025). Machine learning and deep learning in computational finance: A systematic review. arXiv. (arXiv)

Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417. DOI: https://doi.org/10.1111/j.1540-6261.1970.tb00518.x

Gisbert, A., Navallas, B., & Trombetta, M. (2024). The role of financial disclosures in reducing information asymmetry and cost of capital. Accounting in Europe, 21(1), 1–25.

Hashim, W. A. (2025, May). AI-Enhanced Models for Investment Risk Prediction in Financial Markets. In 2025 3rd International Conference on Business Analytics for Technology and Security (ICBATS) (pp.1-8). IEEE.

Hatch, B. C., Johnson, S. A., Wang, Q. E., & Zhang, J. (2021). Algorithmic trading and firm value. Journal of Banking & Finance, 125, 106090. DOI: https://doi.org/10.1016/j.jbankfin.2021.106090

Hendershott, T., Jones, C. M., & Menkveld, A. J. (2011). Does algorithmic trading improve liquidity? The Journal of finance, 66(1), 1-33. DOI: https://doi.org/10.1111/j.1540-6261.2010.01624.x

Hilton, R. W., & Platt, D. E. (2005). Managerial accounting: creating value in a dynamic business environment (p. 864). New York: McGraw-Hill/Irwin.

Imandojemu, K., Osabohien, R., Al-Faryan, M. A. S., & Odebunmi, S. T. (2025). Artificial Intelligence-Driven Algorithmic Trading: Analyzing its impact on Stock Market Volatility in Emerging vs. Developed Economies. Development and Sustainability in Economics and Finance, 100104. DOI: https://doi.org/10.1016/j.dsef.2025.100104

Ismail, T. H., & Obiedallah, Y. R. (2022). Firm performance and cost of equity capital: The moderating role of narrative risk disclosure. Future Business Journal, 8(1), 1–18. DOI: https://doi.org/10.1186/s43093-022-00156-2

Jonathan, D., Burugupalli, S., Uggina, M., Kancherala, H., Chilukuri, G. S. P., Nwanegbo, I. M., & Chiobi, N. F. (2025). Stock Price Prediction Using Machine Learning. International Journal of Engineering Processing and Safety Research. DOI: https://doi.org/10.70382/caijepsr.v8i5.008

Kayed, S., Alta’any, M., Meqbel, R., Khatatbeh, I. N., & Mahafzah, A. (2025). Bank FinTech and bank performance: evidence from an emerging market. Journal of Financial Reporting and Accounting, 23(2), 518-535 DOI: https://doi.org/10.1108/JFRA-09-2023-0526

Kou, G., Olgu Akdeniz, Ö., Dinçer, H., & Yüksel, S. (2021). Fintech investments in banking sector: A hybrid decision-making approach. Financial Innovation, 7(39), 1–28. DOI: https://doi.org/10.1186/s40854-021-00256-y

Li, K., Niskanen, J., & Niskanen, M. (2019). Capital structure and firm performance in European SMEs: does credit risk make a difference?. Managerial Finance, 45(5), 582-601. DOI: https://doi.org/10.1108/MF-01-2017-0018

Li, X., Zhang, Y., & Chen, H. (2024). Machine learning prediction of stock price crash risk. Systems, 12(5), 143. DOI: https://doi.org/10.3390/systems12050143

Lo, A. W. (2004). The Adaptive Market Hypothesis: Market efficiency from an evolutionary perspective. The Journal of Portfolio Management, 30(5), 15–29. DOI: https://doi.org/10.3905/jpm.2004.442611

Ochuba, C. O., Eze, G. P., & Nwankwo, S. I. (2024). Machine learning applications in financial decision-making and market prediction. African Journal of Finance and Technology, 6(1), 23–41.

Ochuba, N. A., Adewumi, A., & Olutimehin, D. O. (2024). The role of AI in financial market development: Enhancing efficiency and accessibility in emerging economies. Finance & Accounting Research Journal.

Ogbulu, O. M. (2018). Oil price volatility, exchange rate movements and stock market reaction: The Nigerian experience (1985-2017). American Finance & Banking Review, 3(1), 12-25. DOI: https://doi.org/10.46281/amfbr.v3i1.200

Ogunleye, O. J., & Akinyomi, O. J. (2022). Capital structure decisions and firm performance in Nigeria. Journal of Finance and Economic Research, 9(1), 76–91.

Ogunleye, O. O., & Akinyomi, O. J. (2022). Cost structure and firm performance in Nigerian listed firms. Nigerian Journal of Accounting Research, 18(1), 112–130.

Oluwayemisi, A. M. B., Elkanah, E., Ademola, O., Olusola, M. O., & Mamidu, A. I. (2022). Cost control and financial performance: an empirical investigation of selected quoted manufacturing firms in Nigeria. The Journal of Accounting and Management, 12(2).

Onyele, K. O., & Nwadike, G. C. (2021). Information asymmetry and stock market development in Nigeria. Journal of Finance and Economic Research, 6(2), 89–104.

Owusu-Ansah, S. (1998). The impact of corporate disclosure on the cost of capital: Evidence from emerging markets. Journal of Accounting and Public Policy, 17(3), 185–211.

Ozordi, E., Uwuigbe, O., Uwuigbe, U., Ojeka, S., & Eluyela, D. (2022). Governance cost and financial service efficiency in Nigeria. Investment Management & Financial Innovations, 19(3), 72. DOI: https://doi.org/10.21511/imfi.19(3).2022.07

Spence, M. (1973). Job market signaling. The Quarterly Journal of Economics, 87(3), 355–374. DOI: https://doi.org/10.2307/1882010

Sule, D. F., & Moloi, T. (2025). How Do Segment Disclosure and Cost of Capital Impact the Investment Efficiency of Listed Firms in Nigeria?. Journal of Risk and Financial Management, 18(5), 258. DOI: https://doi.org/10.3390/jrfm18050258

Sunday, O. (2025). Fintecth Adoption, Financial Inclusion and Bank Performance in Nigeria. Fuoye Journal of Management Science, 3(3).

Taheri Hosseinkhani, N. (2025). Comparative Analysis of Financial Performance among Traditional Quantitative, AI-Based, and Hybrid Modeling Approaches. DOI: https://doi.org/10.2139/ssrn.5403534

Toby, A. J., & Dibiah, S. (2021). Capital market development and economic growth in Nigeria. American International Journal of Economics and Finance Research, 3(1), 16-38. DOI: https://doi.org/10.46545/aijefr.v3i1.155

Yasameen, A. Q., Manhosh, M. M., Al-Khamees, H. A., Srayyih, F. H., Abed, M. K., Al-Sharify, T. A., ... & Hashim, W. A. (2025, May). AI-Enhanced Models for Investment Risk Prediction in Financial Markets. In 2025 3rd International Conference on Business Analytics for Technology and Security (ICBATS) (pp. 1-8). IEEE. DOI: https://doi.org/10.1109/ICBATS66542.2025.11258412