Sahraei, Fatemeh, Jamali, Jafar, Vakilifard, Hamid Reza, Zare, Ali, Zeraatkish, Seyed Yaghoub. (1403). Bankruptcy prediction using the Black-Scholes asset pricing model (Experimental evidence: Tehran Stock Exchange). هنرهای کاربردی, 15(5), 121-142. doi: 10.22075/ijnaa.2023.33026.4385
Fatemeh Sahraei; Jafar Jamali; Hamid Reza Vakilifard; Ali Zare; Seyed Yaghoub Zeraatkish. "Bankruptcy prediction using the Black-Scholes asset pricing model (Experimental evidence: Tehran Stock Exchange)". هنرهای کاربردی, 15, 5, 1403, 121-142. doi: 10.22075/ijnaa.2023.33026.4385
Sahraei, Fatemeh, Jamali, Jafar, Vakilifard, Hamid Reza, Zare, Ali, Zeraatkish, Seyed Yaghoub. (1403). 'Bankruptcy prediction using the Black-Scholes asset pricing model (Experimental evidence: Tehran Stock Exchange)', هنرهای کاربردی, 15(5), pp. 121-142. doi: 10.22075/ijnaa.2023.33026.4385
Sahraei, Fatemeh, Jamali, Jafar, Vakilifard, Hamid Reza, Zare, Ali, Zeraatkish, Seyed Yaghoub. Bankruptcy prediction using the Black-Scholes asset pricing model (Experimental evidence: Tehran Stock Exchange). هنرهای کاربردی, 1403; 15(5): 121-142. doi: 10.22075/ijnaa.2023.33026.4385

Bankruptcy prediction using the Black-Scholes asset pricing model (Experimental evidence: Tehran Stock Exchange)

International Journal of Nonlinear Analysis and Applications
مقاله 11، دوره 15، شماره 5، مرداد 2024، صفحه 121-142    اصل مقاله (893.18 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/ijnaa.2023.33026.4385
نویسندگان
Fatemeh Sahraei1؛ Jafar Jamali* 1؛ Hamid Reza Vakilifard2؛ Ali Zare3؛ Seyed Yaghoub Zeraatkish4
1Department of Financial Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
2Department of Accounting, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
3Department of Law, Faculty of Theology and Political Sciences, Sciences and Research Branch, Islamic Azad University, Tehran, Iran
4Department of Agricultural Economic, Faculty of Agricultural Sciences and Food Engineering, Sciences and Research Branch, Islamic Azad University, Tehran, Iran}
چکیده
The bankruptcy of companies is essential in financial literature, and the development of bankruptcy forecasting techniques and models is the priority of financial research goals. Many studies have been conducted on predicting the bankruptcy of companies. This study first used a combination of theoretical and expert analysis to determine the financial ratios and macroeconomic variables affecting bankruptcy. Thus, bankrupt companies were distinguished from non-bankrupt ones referring to Black and Scholes’s asset pricing models based on the intrinsic value of liabilities and assets. Therefore, 144 companies were studied in the 12 years of 2010-2021 in the screening process. The analysis of multilayer artificial neural networks for evaluating the reliability of the results in identifying the factors affecting the prediction of bankruptcy and prioritizing these factors showed that the least important factor was the ratio of capital to the net profit of the company and the most critical factor was the ratio of profit before interest and taxes to the total assets of the company.
کلیدواژه‌ها
Bankruptcy؛ Expert assessment؛ Black-Scholes Asset pricing model؛ Factors affecting bankruptcy؛ Bankruptcy prediction
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