[1] F. Alizadeh, Investigating factors affecting the decline and bankruptcy of investment companies from the perspective of financial management (Tehran Stock Exchange Organization), Master Thesis, Faculty of Management, Naraq Branch, Islamic Azad University, 2016.
[2] R. Alizadeh, The impact of the dynamics of financial components in predicting the bankruptcy of companies listed on the Tehran Stock Exchange, Master’s Thesis, Sepahan Institute of Higher Education of Science and Technology, Faculty of Humanities, 2014.
[3] E.I. Altman, Financial ratios, discriminant analysis and the prediction of corporate bankruptcy, J. Finance. 23 (1968), no. 4, 589–609.
[4] Gh. Amiri, Evaluating the efficiency of financial crisis prediction models for Iranian companies, Account. Knowledge 1 (2010), no. 2, 158–139.
[5] A.M. Ansari, M. Alinejad Sarukolaei and A. Rahimipour, Investigating the application of Falmer and Springgate bankruptcy forecasting models in companies admitted to the Tehran Stock Exchange, J. Appl. Res. Financ. Report.
2 (2013), no. 2.
[6] M. Bani and H. Mehrpouyan, Investigating the relationship between intellectual capital and its components with the bankruptcy risk of companies listed on the Tehran Stock Exchange according to Altman’s model, Int. Conf. Manag. Econ. Soc. Sci., 2015.
[7] W. Beaver, Financial ratios as predictors of failures, J. Account. Res. 4 (1966), 71–111.
[8] F. Black and M. Scholes, The pricing of options and corporate liabilities, J. Politic. Econ. 81 (1973), no. 3, 637–654.
[9] M. Boyacioglu, Y. Kara and M. Baykan, Predicting bank financial failures using neural networks, support vector machines and multivariate statistical methods: A comparative analysis in the sample of savings deposit insurance fund (SDIF) transferred banks in Turkey, Expert Syst. Appl. 36 (2009), 3355–3366.
[10] M. Ebadi, A. Nemati and A. Ismailzadeh, The effect of conservatism on corporate bankruptcy risk, First Nat. Conf. Position Manag. Account. New World Bus. Econ. Culture, 2014.
[11] S. Esmaili and A. Gogerdchian, Predicting financial bankruptcy using cash flow statement: artificial neural network approach, J. Organ. Culture Manag. 15(4) (2017) 879–901.
[12] M.I. Fadainejad and R. Eskandari, Designing and explaining the prediction model to identify the most important factors in the bankruptcy of companies in the Tehran Stock Exchange, J. Account. Res. 9 (2011), 38–55.
[13] J. Felix and P. Ivan, Bankruptcy visualization and prediction using neural networks: A study of U.S commercial banks, Expert Syst. Appl. 42 (2015), no. 6, 2857–2869.
[14] M.J. Firouzian and N. Najm al-Dini, Application of genetic algorithm in predicting bankruptcy and comparing it with Altman’s Z model in companies admitted to Tehran Stock Exchange, Account. Audit. Rev. 65 (2011), 99–116.
[15] A. Ghadiri Moghadam, M.M. Gholampourfard and F. Nasirzadeh, Investigating the ability of Altman and Ehlson’s bankruptcy prediction models in predicting the bankruptcy of companies admitted to the stock exchange, Knowledge Dev. Mag. 28 (2009), 100–125.
[16] M. Ghatebi et al. Bankruptcy prediction modeling using profit management variables, Econ. Model. Sci. Quart. 14 (2020), no. 50, 131–152.
[17] M. Ghosouri, Predicting bankruptcy of companies using cash flow ratios, Master’s Thesis, Faculty of Management and Accounting, Semnan University, Iran, 2014.
[18] M. Haji Hashem and Z. Amirhosseini, Forecasting bankruptcy and management of companies: the perspective of financial ratios, Quart. Sci. J. Account. Manag. Audit Knowledge 8 (2019), no. 30, 201–220.
[19] A. Irji Rad and S. Deh Bashi, Examining some factors affecting bankruptcy, Third Nat. Account. Financ. Manag. Investment Conf., 2014.
[20] Ch. Jeong, J.H. Min and K. Myung Suk, A tuning method for the architecture of neural network models incorporating GAM and GA as applied to bankruptcy prediction, Expert Syst. Appl. 39 (2012), 3650–3658.
[21] Ch. HungWu, G. Tzeng, Y. Jia Goo and F. Wen-Chang, A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy, Expert Syst. Appl. 32 (2007), no. 2, 397–408.
[22] Y. Jong Sik and Y.S. Kwon, A practical approach to bankruptcy prediction for small businesses: Substitutingthe unavailable financial data for credit card sales information, Expert Syst. Appl. 37 (2010) 3624–362.
[23] J. Kaur, Financial distress identification: Application of Black-Sholes-merton model, J. Commerce Account. Res. 7 (2018), no. 2, 44–55.
[24] F. Kouzegar, The relationship between auditor characteristics and bankruptcy prediction, Master’s Thesis, Shafaq Institute of Higher Education, Account. Department, 2020.
[25] T. Lensberg, A. Eilifsen and Th.E. McKee, Bankruptcy theory development and classification via genetic programming, European J. Oper. Res. 169 (2006), 677–697.
[26] N. Makian, S.M.T. Al-Madrasi; and S. Karimi Teklo, Comparison of artificial neural network model with logistic regression and audit analysis methods in predicting corporate bankruptcy, Econ, Res. Quart. 10 (2010), 161–191.
[27] A.N.K. Mizan and M. Hossain, Mahabbat, Financial soundness of cement industry of bangladesh: an empirical investigation using Z-Score, Amer. J. Trade Policy. 1 (2014), no. 1, 16–22.
[28] S.E. Mirani Anarmarzi and M. Jovanmard Ahandani, Presentation of the decision tree algorithm for predicting the bankruptcy of listed companies, Quart.J. New Res. Approach. Manag. Account. 85 (2022), 1400–1419.
[29] R. Mohseni and S. Rahimian Bangjeh, Bankruptcy prediction using efficiency as a predictor variable based on logit panel data approach, Quart. J. Quant. Econ. 15 (2018), no. 2, 111–130.
[30] K. Myoung-Jong and K. Dae-Ki, Classifiers selection in ensembles using genetic algorithms for bankruptcy prediction, Expert Syst. Appl. 39 (2012), no. 10, 9308–9314.
[31] R. Nasri Nasrabadi, Analyzing the relationships between financial ratios and corporate governance indicators in predicting bankruptcy of companies listed on the Tehran Stock Exchange, Master’s Thesis, University of Isfahan, 2018.
[32] E. Nili Isfahani, Analytical investigation of the factors affecting the decline and bankruptcy of companies from the perspective of failure of financial management, Master’s Thesis, Islamic Azad University, Central Tehran Branch, Faculty of Management, 2011.
[33] D. Olson, L. Dursun Delen and M. Yanyan, Comparative analysis of data mining methods for bankruptcy prediction, Decision Support Syst. 52 (2012), 464–473.
[34] R. Ogachi, P. Ndege, Z. Gaturu and A. Zoltan, Corporate bankruptcy prediction model, a special focus on listed companies in Kenya, J. Risk Financ. Manag. 13 (2020), no. 3, 1–14. [35] A. Pettit and H. Philip, Equity and the Law of Trusts, Oxford, 2012.
[36] B. Pham Vo Ninh Ninh, T. Do Thanh, D. Vo Hong, Financial distress and bankruptcy prediction: An appropriate model for listed firms in Vietnam, Econ. Syst. 42 (2018), no. 4, 616–624.
[37] B. Pham Vo Ninh, T. Do Thanh and D. Vo Hong, Financial distress and bankruptcy prediction: An appropriate model for listed firms in Vietnam, Economic Systems, Elsevier. 42 (2018), no. 4, 616–624.
[38] I. Premachandra, M. Yao Chen and J. Watson, DEA as a tool for predicting corporate failure and success: A case of bankruptcy assessment, Omega 39 (2011), 620–626.
[39] M. Rasoulzadeh, Investigating the use of Altman’s model to predict the bankruptcy of companies listed on the Tehran Stock Exchange, Bors Month. 30 (2001), 62–65.
[40] Sh. Pathan and R. Shams, Does board structure in banks really affect their performance?, J. Bank. Finance 37 (2013), no. 5, 1573–1589.
[41] Y. Shi and X. Li, An overview of bankruptcy prediction models for corporate firms: A Systematic literature review, Intangible Capital 15 (2019), no. 2, 114–127.
[42] H. Vakilifard, N. Pilehvari and S.S. Zaidi, Present a model for predicting companies’ bankruptcy in the Tehran stock exchange using an adaptive neural fuzzy inference system, J. Financ. Engin. Secur. Manag. 5 (2014), no. 18.
[43] S. Vlaovic-Begovic and L. Bonic, Developing a model to predict corporate bankruptcy using decision tree in the Republic of Serbia, Facta Univer. Ser.: Econ. Organ. 17 (2020), no. 2, 127–139.
[44] M.H. Vadiei and S.H. Mirasmaili, Bankruptcy prediction using Ehlson’s logit analysis and Fulmer’s multiple criterion analysis and their comparison, Account. Audit. Res. 13 (2012), 146–172.
[45] M. Younesi and M. Salehi, Theoretical review of the risk model and traditional methods of bankruptcy forecasting,
Second Int. Conf. Manag. and Account. Iran, 2017.
[46] X. Zhang, R. Ouyang, D. Liu and L. Xu, Determinants of corporate default risk in China: The role of financial constraints, Econ. Modell. 92 (2020), 87–98.
[47] Sh. Zarabizadeh, Applied investigation of bankruptcy prediction models of companies listed in Tehran Stock Exchange by using artificial neural network method, Master’s Thesis, Humanities and Social Sciences Campus-Faculty of Economics, Managment and Accounting, Yazd University, 2014.
[48] M.E. Zmijewski, Methodological issues related to the estimation of financial distress prediction models, J. Account. Res. 22 (1984), 59–82.
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