Transactions on Data Analysis in Social Science

Transactions on Data Analysis in Social Science

Evaluation and Comparison of Classification Model Performance in Predicting Corporate Credit Ratings Using Artificial Intelligence: A Case Study of the Tehran Stock Exchange

Document Type : Original Article

Authors
S. Shaghaghi Shahri 1
O. Rahmani Seryasat 2
1 Department of Financial Management, Faculty of Management, Tehran East Branch, Islamic Azad University, Tehran, Iran
2 Assistant Professor, Department of Electrical Engineering, Shams Higher Education Institute, Gorgan, Iran
10.47176/TDASS.2024.109
Abstract
This article examines and evaluates the performance of four classification models in predicting corporate credit ratings. The models under study include Support Vector Machine (SVM), Artificial Neural Network (Neural Network), k-Nearest Neighbors (KNN), and Decision Tree. The data used includes features such as exports, company age, production volume, external auditing, foreign ownership, ownership type, and company size, all extracted from the financial statements of companies listed on the Tehran Stock Exchange. The data was divided into training and testing sets, standardized, and then used for training and evaluating the models. The performance of the models was assessed based on accuracy, precision, recall, ROC AUC score, and confusion matrix. The results indicate that the Decision Tree model, with an accuracy of 1.000 and an ROC AUC score of 1.000, exhibited the best performance in predicting corporate credit ratings. The SVM and Neural Network models demonstrated very good performance with an accuracy of 0.995 and an ROC AUC score of 0.999. The KNN model showed acceptable performance with an accuracy of 0.990 and an ROC AUC score of 0.993. This study demonstrates that classification models can effectively aid in predicting corporate credit ratings, with the Decision Tree model being identified as the best option in this context.
Keywords
Corporate Credit Ratings
Support Vector Machine
Neural Network
k-Nearest Neighbors
Decision Tree
Performance Evaluation
Tehran Stock Exchange
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Transactions on Data Analysis in Social Science
Volume 6, Issue 2
Spring 2024
Pages 109-118

  • Receive Date 15 February 2024
  • Revise Date 22 March 2024
  • Accept Date 12 June 2024