Analyzing the Performance of Machine Learning Algorithms in Pricing Financial Options

A Study on the Tehran Stock Exchange

Authors

  • Assint .Prof. Eslam Fakher Faculty of Economic and Social Sciences, Shahid Chamran University, Ahvaz, Iran
  • Reza Mahdavi Faculty of Economic and Social Sciences, Shahid Chamran University, Ahvaz, Iran
  • Prof. Dr. Ghassan Tareq Dhahir Faculity member of financial and Banking Departmant , Al-Muthanna University

DOI:

https://doi.org/10.34093/zw9gkk61

Keywords:

Pricing Financial Options Contracts, Option Greek, Black-Scholes Model, Machine Learning Algorithms

Abstract

This study compares the performance of machine learning algorithms with the Black-Scholes model in predicting the price of financial options. Data from 153 contracts traded on the Tehran Stock Exchange between April 2018 and July 2024 were used. The models' performance was evaluated using MAE and RMSE metrics, and the results indicated that machine learning algorithms significantly outperformed the Black-Scholes model in terms of prediction accuracy.

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Published

2025-12-31

Issue

Vol. 20 No. 73 (2025): Vol. 20 No. 73 (2025): Journal of Accounting and Financial Studies

Section

Paper research

License

The copyright is transferred to the journal when the researcher is notified of the acceptance of his research submitted for publication in the journal.

How to Cite

Analyzing the Performance of Machine Learning Algorithms in Pricing Financial Options: A Study on the Tehran Stock Exchange. (2025). Journal of Accounting and Financial Studies ( JAFS ), 20(73), 231-244. https://doi.org/10.34093/zw9gkk61