Al-Hmouz, R., Pedrycz, W., & Balamash, A. (2015). Description and prediction of time series: A general framework of Granular Computing. Expert Systems with Applications, 42(10), 4830-4839. doi:10.1016/j.eswa.2015.01.060
Babu, M., N.Geethanjali, & B.Satyanarayana, P. (2012, January 02). Clustering Approach to Stock Market Prediction. Retrieved from http://paper.researchbib.com/view/paper/59204
Bagheri, A., Peyhani, H. M., & Akbari, M. (2014). Financial forecasting using ANFIS networks with Quantum-behaved Particle Swarm Optimization. Expert Systems with Applications, 41(14), 6235-6250. doi:10.1016/j.eswa.2014.04.003
Bao, W., Yue, J., & Rao, Y. (2017). A deep learning framework for financial time series using stacked autoencoders and long-short term memory. Plos One, 12(7). doi:10.1371/journal.pone.0180944
Bengio, Y. (2009). Learning Deep Architectures for AI. Foundations and Trends® in Machine Learning, 2(1), 1-127. doi:10.1561/2200000006
Chong, E., Han, C., & Park, F. C. (2017). Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies. Expert Systems with Applications, 83, 187-205. doi:10.1016/j.eswa.2017.04.030
Ghosh, P., Neufeld, A., & Sahoo, J. K. (2020, April 21). Forecasting directional movements of stock prices for intraday trading using LSTM and random forests. Retrieved from https://arxiv.org/abs/2004.10178
Gunduz, H., Cataltepe, Z., & Yaslan, Y. (2017). Stock market direction prediction using deep neural networks. 2017 25th Signal Processing and Communications Applications Conference (SIU). doi:10.1109/siu.2017.7960512
Hiransha M, Dr. E. A. Gopalakrishnan, Vijay Krishna Menon, Dr. Soman K. P, (2018). NSE Stock Market Prediction Using Deep-Learning Models. Procedia Computer Science, 132, 1351-1362. doi:10.1016/j.procs.2018.05.050
Idrees, S. M., Alam, M. A., & Agarwal, P. (2019). A Prediction Approach for Stock Market Volatility Based on Time Series Data. IEEE Access, 7, 17287-17298. doi:10.1109/access.2019.2895252
Khan, W., Ghazanfar, M. A., Azam, M. A., Karami, A., Alyoubi, K. H., & Alfakeeh, A. S. (2020). Stock market prediction using machine learning classifiers and social media, news. Journal of Ambient Intelligence and Humanized Computing. doi:10.1007/s12652-020-01839-w
Khan, W., Malik, U., Ghazanfar, M. A., Azam, M. A., Alyoubi, K. H., & Alfakeeh, A. S. (2019). Predicting stock market trends using machine learning algorithms via public sentiment and political situation analysis. Soft Computing, 24(15), 11019-11043. doi:10.1007/s00500-019-04347-y
Kimoto, T., Asakawa, K., Yoda, M., & Takeoka, M. (1990). Stock market prediction system with modular neural networks. 1990 IJCNN International Joint Conference on Neural Networks. doi:10.1109/ijcnn.1990.137535
Kusuma, R. M., Ho, T., Kao, W., Ou, Y., & Hua, K. (2019, February 26). Using Deep Learning Neural Networks and Candlestick Chart Representation to Predict Stock Market. Retrieved from https://arxiv.org/abs/1903.12258
Lathuiliere, S., Mesejo, P., Alameda-Pineda, X., & Horaud, R. (2020). A Comprehensive Analysis of Deep Regression. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1-1. doi:10.1109/tpami.2019.2910523
Lee, J., Kim, R., Koh, Y., & Kang, J. (2019). Global Stock Market Prediction Based on Stock Chart Images Using Deep Q-Network. IEEE Access, 7, 167260-167277. doi:10.1109/access.2019.2953542
Liu, G., & Wang, X. (2019). A Numerical-Based Attention Method for Stock Market Prediction With Dual Information. IEEE Access, 7, 7357-7367. doi:10.1109/access.2018.2886367
Minh, D. L., Sadeghi-Niaraki, A., Huy, H. D., Min, K., & Moon, H. (2018). Deep Learning Approach for Short-Term Stock Trends Prediction Based on Two-Stream Gated Recurrent Unit Network. IEEE Access, 6, 55392-55404. doi:10.1109/access.2018.2868970
Nguyen, T., & Yoon, S. (2019). A Novel Approach to Short-Term Stock Price Movement Prediction using Transfer Learning. Applied Sciences, 9(22), 4745. doi:10.3390/app9224745
Parmar, I., Agarwal, N., Saxena, S., Arora, R., Gupta, S., Dhiman, H., & Chouhan, L. (2018). Stock Market Prediction Using Machine Learning. 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC). doi:10.1109/icsccc.2018.8703332
Parmar, I., Agarwal, N., Saxena, S., Arora, R., Gupta, S., Dhiman, H., & Chouhan, L. (2018). Stock Market Prediction Using Machine Learning. 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC). doi:10.1109/icsccc.2018.8703332
Patel, J., Shah, S., Thakkar, P., & Kotecha, K. (2015). Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques. Expert Systems with Applications, 42(1), 259-268. doi:10.1016/j.eswa.2014.07.040
Qiu, J., Wang, B., & Zhou, C. (2020, January 03). Forecasting stock prices with long-short term memory neural network based on attention mechanism. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/31899770
Ren, R., Wu, D. D., & Liu, T. (2019). Forecasting Stock Market Movement Direction Using Sentiment Analysis and Support Vector Machine. IEEE Systems Journal, 13(1), 760-770. doi:10.1109/jsyst.2018.2794462
S Abdulsalam Sulaiman Olaniyi, Adewole, Kayode S. Jimoh, R. G. Stock Trend Prediction Using Regression Analysis – A Data Mining Approach, ARPN Journal of Systems and Software, Volume 1 No. 4, JULY 2011
Selvamuthu, D., Kumar, V., & Mishra, A. (2019). Indian stock market prediction using artificial neural networks on tick data. Financial Innovation, 5(1). doi:10.1186/s40854-019-0131-7
Selvin, S., Vinayakumar, R., Gopalakrishnan, E. A., Menon, V. K., & Soman, K. P. (2017). Stock price prediction using LSTM, RNN and CNN-sliding window model. 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI). doi:10.1109/icacci.2017.8126078
Son, Y., Noh, D., & Lee, J. (2012). Forecasting trends of high-frequency KOSPI200 index data using learning classifiers. Expert Systems with Applications, 39(14), 11607-11615. doi:10.1016/j.eswa.2012.04.015
Stoean, C., Paja, W., Stoean, R., & Sandita, A. (2019). Deep architectures for long-term stock price prediction with a heuristic-based strategy for trading simulations. Plos One, 14(10). doi:10.1371/journal.pone.0223593
Wang, Y., Liu, H., Guo, Q., Xie, S., & Zhang, X. (1970). Stock Volatility Prediction by Hybrid Neural Network: Semantic Scholar. Retrieved from https://www.semanticscholar.org/paper/Stock-Volatility-Prediction-by-Hybrid-Neural-Wang-Liu/310b54f1913ac93cb2817e810c62e92e6a65e326
Yuan, X., Yuan, J., Jiang, T., & Ain, Q. U. (2020). Integrated Long-Term Stock Selection Models Based on Feature Selection and Machine Learning Algorithms for China Stock Market. IEEE Access, 8, 22672-22685. doi:10.1109/access.2020.2969293