Stock values predictions using deep learning based hybrid models

[1]  Jiangtao Ren,et al.  An integrated framework of deep learning and knowledge graph for prediction of stock price trend: An application in Chinese stock exchange market , 2020, Appl. Soft Comput..

[2]  Randall S. Sexton,et al.  Toward global optimization of neural networks: A comparison of the genetic algorithm and backpropagation , 1998, Decis. Support Syst..

[3]  Amir Mosavi,et al.  Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data; a Comparative Analysis , 2020, IEEE Access.

[4]  Anthony T. Chronopoulos,et al.  A review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues , 2020, J. Biomed. Informatics.

[5]  Kuldip K. Paliwal,et al.  Bidirectional recurrent neural networks , 1997, IEEE Trans. Signal Process..

[6]  David Enke,et al.  The use of data mining and neural networks for forecasting stock market returns , 2005, Expert Syst. Appl..

[7]  Aderemi Oluyinka Adewumi,et al.  Stock Price Prediction Using the ARIMA Model , 2014, 2014 UKSim-AMSS 16th International Conference on Computer Modelling and Simulation.

[8]  Benjamin Letham,et al.  Forecasting at Scale , 2018 .

[9]  Cheng Jian,et al.  Life Prediction for Machinery Components Based on CNN-BiLSTM Network and Attention Model , 2020 .

[10]  Michele Marchesi,et al.  A hybrid genetic-neural architecture for stock indexes forecasting , 2005, Inf. Sci..

[11]  Ajith Abraham,et al.  Hybrid Intelligent Systems for Stock Market Analysis , 2001, International Conference on Computational Science.

[12]  Pedram Ghamisi,et al.  Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods , 2020 .

[13]  Inderjit S. Dhillon,et al.  Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization , 2018, ICML.

[14]  Akbar Siami Namin,et al.  The Performance of LSTM and BiLSTM in Forecasting Time Series , 2019, 2019 IEEE International Conference on Big Data (Big Data).

[15]  Sung Wook Baik,et al.  Improving Electric Energy Consumption Prediction Using CNN and Bi-LSTM , 2019, Applied Sciences.

[16]  Ruoyu Chen,et al.  A Text Sentiment Classification Modeling Method Based on Coordinated CNN‐LSTM‐Attention Model , 2019, Chinese Journal of Electronics.

[17]  Changjun Zhou,et al.  Forecasting stock prices with long-short term memory neural network based on attention mechanism , 2020, PloS one.

[18]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[19]  Ha Young Kim,et al.  Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data , 2019, PloS one.

[20]  F. Tay,et al.  Application of support vector machines in financial time series forecasting , 2001 .

[21]  Saman Haratizadeh,et al.  CNNpred: CNN-based stock market prediction using a diverse set of variables , 2019, Expert Syst. Appl..

[22]  Shyh-Jier Huang,et al.  Short-term load forecasting via ARMA model identification including non-Gaussian process considerations , 2003 .

[23]  Shahab S,et al.  Deep Learning for Stock Market Prediction , 2020, Entropy.

[24]  Rohit Choudhry,et al.  A Hybrid Machine Learning System for Stock Market Forecasting , 2008 .

[25]  K. P. Soman,et al.  Stock price prediction using LSTM, RNN and CNN-sliding window model , 2017, 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[26]  Nammee Moon,et al.  BiLSTM model based on multivariate time series data in multiple field for forecasting trading area , 2019, Journal of Ambient Intelligence and Humanized Computing.

[27]  Stefan Lessmann,et al.  Bridging the divide in financial market forecasting: machine learners vs. financial economists , 2016, Expert Syst. Appl..

[28]  Fatih Ecer,et al.  Training Multilayer Perceptron with Genetic Algorithms and Particle Swarm Optimization for Modeling Stock Price Index Prediction , 2020, Entropy.

[29]  P. Franses,et al.  Forecasting stock market volatility using (non‐linear) Garch models , 1996 .

[30]  Yang Bing,et al.  Stock Market Prediction Using Artificial Neural Networks , 2012 .

[31]  Thomas Fischer,et al.  Deep learning with long short-term memory networks for financial market predictions , 2017, Eur. J. Oper. Res..

[32]  Kwok-Wing Chau,et al.  A Survey of Deep Learning Techniques: Application in Wind and Solar Energy Resources , 2019, IEEE Access.