References
(In IEEE Format) [1] J. W. Goodell, “COVID-19 and finance: Agendas for future research,” Finance Research Letters, Vol.35, pp.101512, 2020. [2] A. Zaremba, R. Kizys, D. Y. Aharon, E. Demir, “Infected markets: Novel coronavirus, government interventions, and stock return volatility around the globe,” Finance Research Letters, Vol.35, pp.101597, 2021. [3] M. A. Naeem, E. Bouri, Z. Peng, S. J. H. Shahzad, X. V. Vo, “Asymmetric efficiency of cryptocurrencies during COVID-19,” Physica A: Statistical Mechanics and Its Applications, Vol.565, pp.125562, 2021. [4] J. Choi, “Value at risk and expected shortfall during the COVID-19 market turmoil: A comparison of parametric and non-parametric approaches,” Journal of Risk and Financial Management, Vol.14, Issue.7, pp.326, 2021. [5] Y. Miao, M. Wu, X. Zhao, “Deep learning for risk management in banking: A comprehensive review,” International Review of Financial Analysis, Vol.87, pp.102618, 2023. [6] L. Chen, M. Pelger, J. Zhu, “Deep learning in asset pricing,” Management Science, Vol.68, Issue.3, pp.2029-2054, 2021. [7] W. Jiang, “Applications of deep learning in stock market prediction: Recent progress,” Expert Systems with Applications, Vol.184, pp.115537, 2021. [8] A. M. Ozbayoglu, M. U. Gudelek, O. B. Sezer, “Deep learning for financial applications: A survey,” Applied Soft Computing, Vol.93, pp.106384, 2020. [9] O. B. Sezer, M. U. Gudelek, A. M. Ozbayoglu, “Financial time series forecasting with deep learning: A systematic literature review: 2005–2019,” Applied Soft Computing, Vol.90, pp.106181, 2020. [10] N. Bussmann, P. Giudici, D. Marinelli, J. Papenbrock, “Explainable AI in fintech risk management,” Frontiers in Artificial Intelligence, Vol.3, pp.26, 2021. [11] L. Zhang, C. Aggarwal, G. J. Qi, “Stock price prediction via discovering multi-frequency trading patterns,” In the Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.2141-2149, 2020. [12] Y. Qin, J. Wu, X. Xiao, B. Chen, L. Zhang, “Machine learning and the Chinese stock market: Empirical evidence from the COVID-19 pandemic,” Finance Research Letters, Vol.43, pp.102008, 2021. [13] Y. Huang, L. F. Capretz, D. Ho, “Machine learning for stock prediction based on fundamental analysis,” IEEE Access, Vol.11, pp.23277-23293, 2023. [14] S. P. Chatzis, V. Siakoulis, A. Petropoulos, E. Stavroulakis, N. Vlachogiannakis, “Forecasting stock market crisis events using deep and statistical machine learning techniques,” Expert Systems with Applications, Vol.112, pp.353-371, 2022. [15] J. Sirignano, R. Cont, “Universal features of price formation in financial markets: Perspectives from deep learning,” Quantitative Finance, Vol.19, Issue.9, pp.1449-1459, 2019. [16] Z. T. Ke, B. T. Kelly, D. Xiu, “Predicting returns with text data,” NBER Working Paper No. 26186, National Bureau of Economic Research, 2019. [17] F. Feng, H. Chen, X. He, J. Ding, M. Sun, T. S. Chua, “Enhancing stock movement prediction with adversarial training,” In the Proceedings of the 28th International Joint Conference on Artificial Intelligence, pp.5843-5849, 2019. [18] A. Bucci, “Realized volatility forecasting with neural networks,” Journal of Financial Econometrics, Vol.18, Issue.3, pp.502-531, 2020. IJCSMT [19] H. Zhou, S. Zhang, J. Peng, S. Zhang, J. Li, H. Xiong, W. Zhang, “Informer: Beyond efficient transformer for long sequence time-series forecasting,” Proceedings of the AAAI Conference on Artificial Intelligence, Vol.35, Issue.12, pp.11106-11115, 2021. [20] Y. Li, S. Jiang, L. Zhang, “Stock market forecasting using deep learning and technical analysis: Systematic review,” IEEE Access, Vol.11, pp.14206-14229, 2023. [21] M. F. Dixon, I. Halperin, P. Bilokon, “Machine learning in finance: From theory to practice,” Springer, 2020. [22] P. Bracke, A. Datta, C. Jung, S. Sen, “Machine learning explainability in finance: An application to default risk analysis,” Bank of England Staff Working Paper No. 816, Bank of England, 2019. [23] B. H. Misheva, J. Osterrieder, A. Hirsa, O. Kulkarni, S. F. Lin, “Explainable AI in credit risk management,” Journal of Risk and Financial Management, Vol.14, Issue.6, pp.242, 2021. [24] F. Prenzel, A. Fejza, “Explainable AI for credit risk management,” Journal of Risk and Financial Management, Vol.16, Issue.2, pp.78, 2023. [25] Y. Liu, Y. Kang, C. Xing, T. Chen, Q. Yang, “A secure federated transfer learning framework,” IEEE Intelligent Systems, Vol.35, Issue.4, pp.70-82, 2020. [26] R. Yan, J. Jin, K. Han, “Reinforcement learning for deep portfolio optimization,” Electronic Research Archive, Vol.32, Issue.9, pp.5176-5200, 2024. [27] H. Markowitz, “Portfolio selection,” The Journal of Finance, Vol.7, Issue.1, pp.77-91, 1952.