پیش بینی وقوع بازده منفی سهام با الگوریتم های هوش مصنوعی و ارتباط آن با گزارشگری محافظه کارانه در شرکت های پذیرفته شده در بورس اوراق بهادار تهران

Behera, J., Pasayat, A. K., & Behera, H. (2022). COVID-19 Vaccination Effect on Stock Market and Death Rate in India. Asia-Pacific Financial Markets, 29(4), 651-673. https://doi.org/10.1007/s10690-022-09364-w

Behera, J., Pasayat, A. K., Behera, H., & Kumar, P. (2023). Prediction based mean-value-at-risk portfolio optimization using machine learning regression algorithms for multi-national stock markets. Engineering Applications of Artificial Intelligence, 120, 105843. https://doi.org/10.1016/j.engappai.2023.105843

Chen, J., Wen, Y., Nanehkaran, Y. A., Suzauddola, M. D., Chen, W., & Zhang, D. (2023). Machine learning techniques for stock price prediction and graphic signal recognition. Engineering Applications of Artificial Intelligence, 121, 106038. https://doi.org/10.1016/j.engappai.2023.106038

Guresen, E., Kayakutlu, G., & Daim, T. U. (2011). Using artificial neural network models in stock market index prediction. Expert Systems with Applications, 38(8), 10389-10397. https://doi.org/10.1016/j.eswa.2011.02.068

Kamrani, H., & Abedini, B. (2022). Developing a Model for Detecting Financial Statement Fraud Using Artificial Neural Networks and Support Vector Machines in Companies Listed on the Tehran Stock Exchange. Journal of Accounting and Management Auditing, 41, 285-314.

Karbalaei Mirzai, M. Y., Mir Loohi, S. M., & Khademi, M. (2022). Investigating the Impact of Macroeconomic Variables on the Tehran Stock Exchange Index: A Comparison of Neural Network and VAR Regression Models. Iranian Political Sociology Monthly, 5(9), 1472-1489. https://civilica.com/doc/1702928/

L.Lima, M., Nascimento, T. P., Labidi, S., Timbo, N. S., Batista, M. V. L., Neto, G. N., Costa, E. A. M., & Sousa, S. R. S. (2016). Using Sentiment Analysis for Stock Exchange Prediction. International Journal of Artificial Intelligence & Applications, 7(1), 59-67. https://doi.org/10.5121/ijaia.2016.7106

Nahdhiyah, A. I. (2023). The Effect of Profitability, Liquidity, Leverage, Company Size and Assets Growth on Stock Return: Empirical Evidence From Indonesia. Maksimum, 13(1), 50. https://doi.org/10.26714/mki.13.1.2023.50-58

Qian, Y. (2023). Progress of the Study on the Impact of Investor Sentiment on Stock Returns. BCP Business & Management, 39, 106-111. https://doi.org/10.54691/bcpbm.v39i.4030

Rezaei, M., & Hosseini, A. (2019). Application of Machine Learning Algorithms in Predicting Stock Returns on the Tehran Stock Exchange. Iranian Journal of Financial and Economic Sciences, 23(1), 57-74.

Riwayati, H. E. (2023). The Effectiveness of Liquidity, Solvency, and Profitability Ratios Against the Stock Returns of the Company. Mix Jurnal Ilmiah Manajemen, 13(3), 600. https://doi.org/10.22441/jurnal_mix.2023.v13i3.006

Sethy, T. K. (2024). A New Method for Estimating Liquidity and Stock Returns in Indian Stock Market. China Accounting and Finance Review, 26(2), 253-275. https://doi.org/10.1108/cafr-05-2023-0052

Shaghaghi Shahri, S. (2024). Evaluation and Comparison of Classification Model Performance in Predicting Corporate Credit Ratings Using Artificial Intelligence: A Case Study of the Tehran Stock Exchange. Transactions on Data Analysis in Social Science, 6(2), 31-44. https://www.transoscience.ir/article_200776.html

Syukur, A., & Istiawan, D. (2021). Prediction of LQ45 Index in Indonesia Stock Exchange: A Comparative Study of Machine Learning Techniques. International Journal of Intelligent Engineering and Systems, 14(1), 453-463. https://doi.org/10.22266/ijies2021.0228.42

Tarasi, M., Banitalebi, B., & Zamani, B. (2019). Forecasting Fraudulent Financial Reporting Through Artificial Neural Network. Management accounting, 12(40), 63-79. https://www.magiran.com/paper/1948354

Vaghfi, S. H. (2019). Application of artificial intelligence algorithms in predicting bankruptcy using macroeconomic and accounting variables in companies listed on the Tehran Stock Exchange. Quarterly of Decision Making and Operations Research, 4(2).

Ye, C., Song, X., & Liang, Y. (2023). Corporate sustainability performance, stock returns, and ESG indicators: fresh insights from EU member states. Environmental Science and Pollution Research, 29. https://doi.org/10.1007/s11356-022-20789-8