10.57647/amc.2026.100110

Providing an Adaptive Model for Pricing Option Contracts in Iran's Capital Market

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  • Mehrdad Miri,
  • Jalal Seifoddini1,
  • Reza Nemati Koshteli*2,
  • Abdollah Rajabi Khanghah1,
  • Nader Naghshineh1,
  1. Department of Financial Engineering, Isl.C. Islamic Azad University, Islamshahr, Iran
  2. Department of Accounting, Isl.C. Islamic Azad University, Islamshahr, Iran

Received: 2026-02-08

Revised: 2026-03-08

Accepted: 2026-04-13

Published in Issue 2026-06-30

Copyright (c) 2026 Mehrdad Miri, Jalal Seifoddini, Reza Nemati Koshteli, Abdollah Rajabi Khanghah, Nader Naghshineh (Author)

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Miri, M., Seifoddini, J., Nemati Koshteli, R., Rajabi Khanghah, A., & Naghshineh, N. (2026). Providing an Adaptive Model for Pricing Option Contracts in Iran’s Capital Market. Agricultural Marketing and Commercialization, 10(1). https://doi.org/10.57647/amc.2026.100110
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Abstract

This research aims to provide an adaptive framework for pricing option contracts in Iran’s capital market by comparing several widely recognised option pricing models, including the Black–Scholes, Heston, Bi-Heston, Binomial Tree, and Trinomial Tree models. These models were selected because they represent the most frequently applied frameworks in both developed and emerging markets, with the Heston and Bi-Heston models incorporating stochastic volatility features that make them suitable for economies experiencing inflation and market instability, such as Iran. The need for this comparative analysis stems from the increasing volume of option trading and the inadequacy of the currently used Black–Scholes model in reflecting Iran’s economic and inflationary conditions. The proposed adaptive approach, presented in the Methodology section, tests these models on data from the Tehran Stock Exchange (2018–2023) and evaluates their performance using RMSE and MAPE error metrics to identify the model that produces the most accurate price estimates. Data related to selected call option symbols (Shesta, Khodro, Khsapa, and Ahrom), filtered based on the highest trading volume and value, were analyzed using Python software and its NumPy and Pandas libraries. Based on the results obtained from the data analysis of the selected symbols, the Trinomial Tree model and the Badestein model showed significantly less error compared to the Black-Scholes model in estimating the market price of option contracts. The research findings indicate the significant superiority of the Trinomial Tree and Badestein models over the commonly used Black-Scholes model in Iran's capital market. Employing these more accurate models can lead to more efficient pricing of option contracts and reduce the gap between theoretical value and market price.

Keywords

  • Option Contracts,
  • Pricing Model,
  • Black-Scholes Model,
  • Badestein Model,
  • Trinomial Tree
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