Journal of Industrial and Systems Engineering

Journal of Industrial and Systems Engineering

Artificial Intelligence Approaches for Performance Prediction of Investment Companies in the Iranian Capital Market

Document Type : Research Paper

Authors
Seyed Milad Mokhtari 1
Ali Zabihi 1
Khosro Faghani Makrani 2
1 Department of Accounting, Sari Branch, Islamic Azad University, Sari, Iran
2 Department of Accounting, Semnan Branch, Islamic Azad University, Semnan, Iran
Abstract
Investment companies listed on the Iranian Stock Exchange play a crucial role within the nation's capital market. Consequently, the development of a robust model for identifying, evaluating, and ranking these companies using artificial intelligence (AI) techniques offers a valuable approach to enhancing investment quality. This study employs AI models to assess and rank investment companies listed on the Iranian Stock Exchange. Specifically, an Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm is proposed. Input variables, encompassing company management characteristics, capital market financial metrics, internal control quality, industry factors, competitive landscape, management quality, credit and economic status, accrual financial ratios, cash financial ratios, and capital market ratios, are utilized. Each input variable undergoes a fuzzification process, involving the definition of membership functions. An ANFIS model is then constructed, utilizing these ten input variables—company management characteristics (Management), capital market financial variables (Financial), internal control quality (IQC), industry factors (Industry), competitive situation (Competitive), quality management (QM), credit and economic situation (CES), accrual financial ratios (AFR), cash financial ratios (CFR), and capital market ratios (CMR)—to predict the performance of investment companies (Performance) as the output variable. The performance of the ANFIS model is subsequently compared with that of a neural network. The results indicate that the ANFIS method outperforms the neural network.
Keywords
Artificial Intelligence
Stock Exchange
Prediction
ANFIS
Subjects
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Journal of Industrial and Systems Engineering
Volume 17, Issue 2 - Serial Number 2
Spring 2025
Pages 250-262

  • Receive Date 19 March 2025
  • Revise Date 09 April 2025
  • Accept Date 20 April 2025