CORPORATE BANKRUPTCY PREDICTION BASED ON HYBRID INTELLIGENT SYSTEMS

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GHAZANFARI MEHDI; RAHIMIKIA EGHBAL; ASKARI ALI

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Journal: The Financial Accounting and Auditing Researches Year:2018 | Volume:10 | Issue:37 Page(s): 159-193

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Title

CORPORATE BANKRUPTCY PREDICTION BASED ON HYBRID INTELLIGENT SYSTEMS

Author(s)

GHAZANFARI MEHDI | RAHIMIKIA EGHBAL | ASKARI ALI | Issue Writer Certificate

Keywords

BANKRUPTCY PREDICTIONQ2

FINANCIAL DISTRESSQ2

DATA MININGQ1

ARTIFICIAL INTELLIGENCEQ1

HYBRID INTELLIGENT SYSTEMQ1

Abstract

Due to the competitiveness of nations' economies and the recent financial crisis at both national and international levels, the need for an effective model to predict the bankruptcy of domestic companies is felt more than ever. Macroeconomic decision makers, economic agencies, and the banking system can benefit from this modeling to make more accurate decisions and reduce undesired outcomes. These models can also be used at the microeconomic level to help with decision-making for future investments.In this research, by implementing an intelligent and coherent system based on Artificial Neural Network (ANN), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and utilizing Imperialist Competitive Algorithm (ICA), Cultural Algorithm (CA) and Harmony Search (HS), we have attempted to improve on the shortcomings of existing models used internationally. Furthermore, in a joint effort with the Iranian National Tax Administration (INTA), the evaluation scale has been extended to incorporate nationwide data which makes the scope of the work unprecedented in the world. The number of examined samples are 5825 and 4089 respectively in the food and textile sectors, and by applying bankruptcy criteria 999 and 848 samples were detected as bankrupt companies. We found the best performance in the combination of support vector machine with harmony search and imperialist competitive algorithm in terms of not using outlier detection.

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APA: Copy

GHAZANFARI, MEHDI, RAHIMIKIA, EGHBAL, & ASKARI, ALI. (2018). CORPORATE BANKRUPTCY PREDICTION BASED ON HYBRID INTELLIGENT SYSTEMS. THE FINANCIAL ACCOUNTING AND AUDITING RESEARCHES, 10(37 ), 159-193. SID. https://sid.ir/paper/198022/en

Vancouver: Copy

GHAZANFARI MEHDI, RAHIMIKIA EGHBAL, ASKARI ALI. CORPORATE BANKRUPTCY PREDICTION BASED ON HYBRID INTELLIGENT SYSTEMS. THE FINANCIAL ACCOUNTING AND AUDITING RESEARCHES[Internet]. 2018;10(37 ):159-193. Available from: https://sid.ir/paper/198022/en

IEEE: Copy

MEHDI GHAZANFARI, EGHBAL RAHIMIKIA, and ALI ASKARI, “CORPORATE BANKRUPTCY PREDICTION BASED ON HYBRID INTELLIGENT SYSTEMS,” THE FINANCIAL ACCOUNTING AND AUDITING RESEARCHES, vol. 10, no. 37 , pp. 159–193, 2018, [Online]. Available: https://sid.ir/paper/198022/en

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