طراحی مدلی برای ارزیابی ریسک اعتباری مشتریان ضمانت‌نامه‌های صادر شده توسط صندوق ضمانت صادرات ایران با کمک مدل شبکه عصبی مصنوعی

References

Abbasian, E., Ebrahimi, M., & Farzanegan, E. (2015). Optimal design of securitization in a principal-agent relationship based on Bayesian inference for moral hazard. Financial Research Journal, 17(1), 123-140. doi: 10.22059/jfr.2015.50708 (in Persian)

Angelini, E., Di Tollo, G., & Roli, A. (2008). A neural network approach for credit risk evaluation. The quarterly review of economics and finance, 48(4), 733-755.

Baghbabi, G., & Eskandari, F. (2017). Estimation of Input & Output Cash of Tejarat Branches in order to Calculate Branches’ Required Cash Via Multivariate Bayesian Clustering Analysis and the Implementation in Neural Network. Financial Research Journal, 19(1), 41-60. doi: 10.22059/jfr.2017.60152 (in Persian)

Bagheri, N. & Haghshenas Kashani, F. (2018). Credit Risk Assessment of Urban Cooperatives Using Neural Network Method. Journal of Urban Economics and Management, 6 (24), 17-33. (in Persian)

Bekhet, H. A., & Eletter, S. F. K. (2014). Credit risk assessment model for Jordanian commercial banks: Neural scoring approach. Review of Development Finance, 4(1), 20-28.

Binici, M. & Hutchison, M. (2018). Do credit rating agencies provide valuable information in market evaluation of sovereign default Risk? Journal of International Money and Finance, 85, 58-75.

Dendramis, Y., Tzavalis, E. & Adraktas, G. (2018). Credit risk modelling under recessionary and financially distressed conditions. Journal of Banking & Finance, 91, 160-175.

Fallahpour, S. & Hakimian, H. (2019). Paired Trading Strategy Optimization Using the Reinforcement Learning Method: Intraday Data of Tehran Stock Exchange. Financial Research Journal, 21(1), 19-34. doi: 10.22059/frj.2018.138913.1006099 (in Persian)

Ghasemi, A.R. & Donyaee, T. (2016). Assessing Credit Risk Rating With Artificial Neural Network Method (The Case of an Iranian Bank). Financial Engineering and Securities Management (Portfolio Management), 7(27), 155-181. (in Persian)

Ghodsypour, S.H., Salari, M. & Delavari, V. (2012). Using Fuzzy Analytic Hierarchy Process and Hybrid of Higher Order Neural Network for Evaluation Credit Risk of Corporate. International Journal of Industrial Engineering and Production Management (International Journal of Engineering Science), 23(1), 44-54. (in Persian)

Hosseini, S. A. & & Zibaei, M. (2015). Credit risk management in agricultural bank of mamasani using neural network model. Iranian Journal of Agricultural Economics (Economics and Agriculture Journal), 9(2), 103-119. (in Persian)

Khashman, A. (2009). A neural network model for credit risk evaluation. International Journal of Neural Systems, 19(04), 285-294.

Khashman, A. (2010). Neural networks for credit risk evaluation: Investigation of different neural models and learning schemes. Expert Systems with Applications, 37(9), 6233-6239.

Khorrami, A., Taghavifard, M. T., & Khatami Firouzabadi, S. M. A. (2020). Credit Status Assessment of Bank Loan Applicants Using CBR Method. Industrial Management Studies, 18(59), 79-116. doi: 10.22054/jims.2018.18574.1660 (in Persian)

Nadalizadeh, A., Hojabr Kiani, K., Hoseini, Sh., Peykarjou, K. (2021). The Asymmetric Effects of Oil Price Shocks on Bank Credit Risk in Iran. QJER, 21(1), 63-92. (in Persian)

Nazarpur, M. N. & Oulad, M. (2018). Prioritizing Influenced Factors on adverse selection and moral hazard in Usury Free Banking (Case study: Bank of Industry and Mining). Islamic Economics, 18(69), 173-199. (in Persian)

Nilsaz, H., Rasekh, A., Osareh, A., & Sinae, H. (2007). Using Neural Networks to Classify the Personal Loan Applicants. Iranian Journal of Economic Research, 9(32), 85-109.
(in Persian)

Pourebadollahan Covich, M., Nobahar, E. & Rahimi, P. (2021). The Impact of Adverse Selection and Moral Hazard on Non-performing Loans of Iran’s Banking System. Monetary & Financial Economics, 27(20), 27- 46. (in Persian)

Shavvalpour, S. & Ashari, E. (2013). Determining the Relationship between Credit Risk & Profitability in Iranian Banks. Financial Research Journal, 15(2), 229-246. doi: 10.22059/jfr.2013.51079 (in Persian)

Sindhuraj, I. C. G. L., & Patrick, A. J. (2023). Loan eligibility prediction using adaptive hybrid optimization driven-deep neuro fuzzy network. Expert Systems with Applications, 224, 119903.‏

Yeh, C. C., Lin, F. & Hsu, C. Y. (2012). A hybrid KMV model, random forests and rough set   theory approach for credit rating. Knowledge-Based Systems, 33, 166-172.

Zhang, X., Ma, Y. & Wang, M. (2023). An attention‐based Logistic‐CNN‐BiLSTM hybrid neural network for credit risk prediction of listed real estate enterprises. Expert Systems, e13299.