نقش نسبت‎های مالی تصویری در پیش‌بینی ورشکستگی شرکت‌ها با استفاده از مدل شبکه‌های عصبی کانولوشن و مقایسه آن با مدل‌های سنتی

References

Agarwal, A. and Patni, I. (2019) Bankruptcy Prediction Models: An Empirical Comparison. International Journal of Innovative Technology and Exploring Engineering (IJITEE) 8(6S2), 131- 139.

Ahmadi Amin, E., & Tahriri, A. (2019). The Effect of Bankruptcy Contagion on Earnings Informativeness. Journal of Accounting and Auditing Review, 26(1), 1-18. (in Persian)

Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy, The Journal of Finance 23 (4), 589-609.

Asgari Alouj, H., Nikbakht, M.R., Karami, GH., & Momeni, M. (2019). Development of the Beneish Model by Combining Artificial Neural Network and Particle Swarm Optimization Algorithm for Earnings Management Prediction. Accounting and Auditing Review, 26(4), 615-638. (in Persian)

Ashoori, M. R. (2019). Picture, Viki (free and online dictionary), design and Advertising. Available in:  www.agerin.ir. (in Persian)

Bagheri, H. A. and Khodaee, A. (2018) Deep learning in MATLAB with machine learning, neural networks and Artificial Intelligence. (in Persian)

Dehkhoda, A.A. (2019). Persian Dictionary,  Vol. 1, (1^th ed). University of Tehran Publishing. (in Persian)

Ding, X., Zhang, Y., Liu, T., Duan, J. (2015). Deep learning for event-driven stock prediction. Proceedings of the 24th International Joint Conference on Artificial Intelligence, 2327–2333.

Ebrahimi Kordlor, A., Arabi, M. (2011). Application of Bankruptcy Predictive Models (Altman, Falmer, Springit, Zimski & Shirata) to Predicting Failure to Grant Companies to the Tehran Stock Exchange (Case Study: Bank Sepah). Accounting and Auditing Research, 3(12), 52-63. doi: 10.22034/iaar.2011.104712

Ghazanfari, M., Rahimikia, E. and Askari, A. (2018). Bankruptcy prediction of companies based on hybrid intectual systems. Quarterly journal of financial accounting and auditing, 10(37), 159-194. (in Persian)

Goehring, M. (2007). Balance sheets: Getting the picture of your Co-ops financial position. www.columinate.coop

Hardinata, L., Warsito, B. and Suparti, S. (2017). Bankruptcy prediction based on financial ratios using Jordan Recurrent Neural Networks: a case study in Polish companies. Journal of Physics: Conference Series, 1025(1), 012098.

Hasanpoor, S. H. (2016). Convolutional Networks. Section one. www.forum.ustmb.ir

Hosaka, T. (2018). Bankruptcy prediction using imaged financial ratios and convolutional neural networks. Available in: https://www.rs.tus.ac.jp/hosaka-t/img/file3.pdf

Hu, H., Tang, L., Zhang, Sh. and Wang, H. (2018). Predicting the direction of stock markets using optimized neural networks with Google Trends, Neuro computing, 285, 188-195, ISSN 0925-2312, https://doi.org/10.1016/j.neucom.2018.01.038.

Jadhav, S., Dange, B. & Shikalgar, S. (2018). Prediction of Stock Market Indices by Artificial Neural Networks Using Forecasting Algorithms. In International Conference on Intelligent Computing and Applications (pp. 455-464). Springer, Singapore.

Jordin, D.P. (2018). Failure pattern – based ensembles applied to bankruptcy forecasting. Journal of Decision Support Systems, 107, 64-77.

Kordestani, Gh. and Tatli, R. (2014). The Evaluation of prediction ability of Bankruptcy models: primary versus adjusted models. Auditing Knowledge Journal, 55, 51-70.    

Krizhevsky, A., Sutskever, I., Hinton, G.E. (2012). Imagenet classification with deep convolutional neural networks. Proceedings of Neural Information Processing Systems.

Lin, M., Chen, Q., Yan, S. (2013). Network in network. arXiv:1312.4400

Marcjasz, G., Uniejewski, B. & Weron, R. (2018). On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks. International Journal of Forecasting, 35(4), 1520-1532.

Mohammadi, Sh., Raeie, R. & Rahimi, R. (2018). Interval Forcasting for Gold Price with hybrib model of ARIMA and Artificial Neural Network. The Journal of Portfolio Management and Financial Engineering, (34), 335-357. (in Persian)

Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 18 (1), 109–131.

Sarafraz, S., Sefati, F. and Ghiasvand, A. (2016). Predicting stock prices with hybrid market indices using a fuzzy neural model. International Conference on Modern Research in Management, Economics and Accounting. (in Persian)

Soleimany, G. (2012). Investigating of the Efficiency of Financial Distress Prediction Models in Iranian companies. Accounting Knowledge, 1(2), 139- 160. (in Persian)

Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., Rabinovich, A. (2015). Going deeper with convolutions. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

Tan, L., Wang, S. & Wang, K. (2017). A new adaptive network-based fuzzy inference system with adaptive adjustment rules for stock market volatility forecasting. Information Processing Letters, 127, 32-36.

Vaez-Ghasemi, M. & Ramezanpour Chardeh, S. (2018). Predicting bankruptcy of companies listed on the Stock Exchange using the artificial neural network. The Journal of Investment Knowledge, (26), 277-296. (in Persian)