Ahmadi,S. Sh. (2016). Investigating the Relationship between Corporate Governance and Systematic Risk with Financial Distress in Companies Accepted in Tehran Stock Exchange, Master's Thesis.
Ahmadi Amin, E., and Tahriri, A. (2019). The Effect of Bankruptcy Contagion on
Earnings Informativeness. Journal of Accounting and Auditing Review, 26 (1), pp. 1-18. (In Persian)
Altman,E.I., (1968). Financial ratios, discriminant analysis and prediction of corporate bankruptcy. Journal of Finance, 23, pp. 589-609.
Asgarnezhad Nouri, B., and Soltani, M. (2015). Designing a BankruptcyPrediction Model Based on Account, Market and Macroeconomic Variables (Case Study: Cyprus Stock Exchange), Iranian journal of management, 9 (1), winter 2016, pp. 125-147
Mullahi E., and Khidozzi, B. (2015). The Effect of Liquidity Level on the Risk of Financial Distress in Companies Accepted in Tehran Stock Exchange, Industrial Management (Azad Sanandaj), No. 34
Bredart, X. (2014). Financial Distress and Corporate Governance around Lehman Brothers Bankruptcy. International Business Research, 7 (5), pp. 1-8
Brewer, B. E., Wilson, C.A., Featherstone, A. M., Harris, J.M., Erickson, K. and Hallahan, (2012). Measuring the Financial Health of U.S. Production Agriculture.
Chang, C. (2009). The Corporate Governance Characteristics of Financially Distressed Firms: Evidence from Taiwan. The Journal of American Academy of Business, 15 (1), pp. 125-132.
Chen, M.Y. (2011). Predicting corporate financial distress based on integrationof decision tree classification and logistic regression. Expert Systems with Applications, 38 (9), pp. 11261-11272.
Eliezer F., Steve S. (2008). Can corporate governance save distressed firms from bankruptcy? An empirical analysis. Review of Quantitative Finance and Accounting, 30 (2), pp. 225-251.
Esmaeelzadeh Moghri, A., and Shakeri, H. (2015). Predicting financial distress of companies listed in Tehran Stock Exchange using simple Bayesian network and comparing it with data envelopment analysis. Journal of Financial Engineering and Portfolio Management, spring 2015, No. 22, pp. 1-28
Felipe Fontaine Rezende ,. Roberto Marcos da Silva Montezano, Fernando Nascimento de Oliveira, Valdir de Jesus Lameira. (2017). Predicting financial distress in publicly-traded companies, Revista Contabilidade & Finanças, vol.28 no.75 São Paulo Sep./Dec. 2017 Epub July 20, 2017.
Fakhrehosseini, F.,and Aghaei Meybodi, O. (2019). Prediction and Identification of Companies with High Bankruptcy probability in Tehran Stock Exchange (Different analysis of models), Journal of Decisions and operations research, 4 (1), summer 2019, Page 3-15(IN PERSIAN).
Fulmer H Score. )1984) is a bankruptcy classification model, based on the 1984 paper "A Bankruptcy Classification Model for Small Firms.
Ghasemi, M., and Ramezanpour, s. (2018). Prediction of Bankruptcy of Companies Listed on the Securities and Exchange Organization Using Artificial Neural Network, Journal of Investment Knowledge, 7 (27), pp. 227-296(IN PERSION).
Hu, H., and Sathye, M. (2015). Predicting Financial Distress in the Hong Kong Growth Enterprises Market from the Perspective of Financial Sustainability. Sustainability, 7, pp. 1186-1200.
James A. Ohlson (1980). Financial Ratios and the Probabilistic Prediction of BankruptcyJournal of Accounting ResearchVol. 18, No. 1 (spring, 1980), pp. 109-131.
Kingsley Opoku, A., Amon Chizema. (2016). The impact of board quality and nomination committee on corporate bankruptcy, Advances in Accounting, incorporating Advances in International Accounting, journal homepage: www.elsevier.com/locate/adiacpp1-7
Kim, C.-S., Mauer, D.C., and Sherman, A.E. (1998). The determinants of corporateliquidity: theory and evidence. Journal of Financial and Quantitative Analysis, 33, 305–334.
Khajavi, SH., and Ghadirian Arani, M. H. (2018). Journal of accounting knowledge, Article 2, 9 (1), pp. 35-61 (IN PERSAN).
Kritsonis, Alicia. (2005). Assessing a firms future financial health. International Journal of Scholarly Academic Intellectual Diversity, California State University vo.8, No.1.
Li, Z., Crook, J., and Andreeva, G. (2015). Corporate Governance and Financial Distress: a Discrete Time Hazard Prediction Model, Retrieved fromhttp://ssrn.com/abstract=2635763.
Maheswara Reddy, D., and Reddy, C. R. (2011). Application of Z score Analysis in EvaluatingThe Financial Health of Pharmaceutical Companies- Acase Study.
Mashayekhi, B., and Ganji, H. (2014). Examining the impact of earnings quality on bankruptcy prediction using artificial neural network. Financial Accounting and Auditing Research, Article 6, 6 (22), pp. 147-173.
Mohd Norfian, A., Norhana, S., and Ismail, A. (2013). Prediction of financial distress companies in the consumer products sector in Malaysia. Journal Sains Humanika, 64 (14).
Marko Robnik-ŠikonjaIgor, K. (1997). Theoretical and Empirical Analysis of ReliefF and RReliefF Machine Learning Volume 53 (1-2), pp 23–69.
Mohd Norfian, A. (2014). Prediction of financial distress companies in the trading and services sector in Malaysia using macroeconomic variables, Journal.
Meshki Miavaghi, M., and Hashemi, M. (2015). Investigating the Relationship between Corporate Governance with Bankruptcy Probability in Companies Listed in Tehran Stock Exchange,The Journal of Research Accounting. 2 (17), pp. 37-58.
Michael E. Tipping (2001) Sparse Bayesian Learning and the Relevance Vector Machine, Journal of Machine Learning Research 1, pp. 211-244.
Outecheva, N. (2007). Corporate Financial Distress: An Empirical Analysis of Distress Risk. University of St. Gallen, Switzerland
Osmani Qasim, M., Javid, D., and Rahimi, Saeed. (2011). Investigating the deterrence impact of corporate governance mechanisms on financial distress in companies listed in Tehran Stock Exchange. Accounting and Auditing Research, No. 12, pp. 1-19.
Owens, E. (2017). Asymmetric Effects of Default Probability on Earnings Informativeness. The University of North Carolina at Chapel Hill. https://ssrn.com/abstract=1869108.
Ozkan, A., and Ozkan, N. (2004). Corporate cash holdings: an empiricalinvestigation of UK companies. Journal of Banking and Finance, 28, pp. 2103–2134.
Pindado, J., Rodrigues, L., and de la Torre, C. (2008). Estimating financial distresslikelihood. Journal of Business Research, 61, pp. 995-1003.
Rahimian, N., Tavakolnia, E. (2013). Financial leverage and its relationship with financial distress and growth opportunities in companies listed in Tehran Stock Exchange (linear and curvature relationships); Quarterly of Financial Accounting, 5 (20), pp. 108-129.
Returns Pengjie Gao Christopher A. Parsons Jianfeng Shen (2017). Global Relation between Financial Distress and Equity. The Review of Financial Studies, hhx060, DOI: 10.1093/rfs/hhx060 Published: 14 June 2017.
Sadeghi, H., Rahimi, P., and Salmani, Y. (2013),The Effect of Macroeconomic and Governance Factors on Financial Distress i Manufacture Firms Listed in Tehran Stock Exchange, Financial monetary economics, 21 (8), pp. 107-127.
Saeedi, Ali. Aghaei, Arezoo. (2009). A Review of Bankruptcy Prediction Methods and Models, Accounting Knowledge and Research, No 16
Setayesh ,M. H., and Mansouri., Sh. (2014). The comparative investigation of corporate governance mechanisms in financial distressed and nonfinancial distressed listed companies of Tehran Stock Exchange. Journal oh financial Research, Volume 16, Issue 1 (Spring and Summer), Page 99-112
Shirata, C.Y. (1995). Read the Sign of Business Failure. Journal of Risk and Management, Vol. 23, pp.117-138.
Springate, G. L. V. (1978). Predicting the possibility of failure in a Canadian firm (Unpublished master’s thesis). Simon Fraser University, Canada
Sun, J., Jia, M-Y., and Li, H. (2011). AdaBoost ensemble for financial distress prediction: An empirical comparison with data from Chinese listed companies.Expert Systems with Applications, 38 (8), pp. 9305-9312.
Thomas J.George,Chuan-Yang Hwang (2010). A resolution of the distress risk and leverage puzzles in the cross section of stock returns" .Journal of Financial Economics (96), pp. 56-79.
Wing Yu, i., Ho, F., Law, E. and Fung, L. (2003). An Analysis of the Financial Health of Hong Kong Corporations.
Xie, C. and C. Luo, and X. Yu. (2011). Financial distress prediction based on SVM and MDA methodes: the case of Chinese listed companies. Quality and quantity, 45 (3), pp. 671-686.
Yang, J.; and Y. Jiang. (2008). Accounting information quality, free cash flow and Overinvestment: A Chinese study. The Business Review, Vol. 11, pp. 159-166
Zmijewski M.E. (1984). Method logical Issues Relate to the Estimation of Financial Distress prediction Models. Journal of Accounting Research, Vol 22 supplement.
Zavgren, C. (1985). Assessing the vulnerability to failure of American industrial firms: A logistic analysis. Journal of Business Finance & Accounting, 12 (1), pp. 19–45.
Zohra, K. F., Mohamed, B., Elhamoud, T., Garaibeh, M., Ilhem, A., and Naimi,H. (2015). Using Financial Ratios to Predict Financial Distress of Jordanian Industrial Firms, ''Empirical Study Using Logistic Regression''. Academic Journal of Interdisciplinary Studies, 4 (2), pp. 137-142.