Forecasting stock price index movement using a constrained deep neural network training algorithm

[1]  E. Fama.  EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* , 1970 .

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

[3]  Kok-Chin Khor,et al.  StockProF: a stock profiling framework using data mining approaches , 2016, Information Systems and e-Business Management.

[4]  Jorge J. Moré,et al.  Digital Object Identifier (DOI) 10.1007/s101070100263 , 2001 .

[5]  Ning Chen,et al.  Financial credit risk assessment via learning-based hashing , 2017, Intell. Decis. Technol..

[6]  Binoy B. Nair,et al.  An intelligent recommender system for stock trading , 2015, Intell. Decis. Technol..

[7]  Chulwoo Han,et al.  Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies , 2017, Expert Syst. Appl..

[8]  Ömer Kaan Baykan,et al.  Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange , 2011, Expert Syst. Appl..

[9]  Roy Rada,et al.  Intelligent technologies for investing: A review of engineering literature , 2008, Intell. Decis. Technol..

[10]  Ritika Singh,et al.  Stock prediction using deep learning , 2016, Multimedia Tools and Applications.

[11]  Yung-Keun Kwon,et al.  An Empirical Study on Importance of Modeling Parameters and Trading Volume-Based Features in Daily Stock Trading Using Neural Networks , 2018, Informatics.

[12]  Yurong Liu,et al.  A survey of deep neural network architectures and their applications , 2017, Neurocomputing.

[13]  Victor Chang,et al.  An innovative neural network approach for stock market prediction , 2018, The Journal of Supercomputing.

[14]  Ioannis E. Livieris,et al.  Improving the Classification Efficiency of an ANN Utilizing a New Training Methodology , 2018, Informatics.

[15]  Jorge Nocedal,et al.  Remark on “algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound constrained optimization” , 2011, TOMS.

[16]  Jürgen Schmidhuber,et al.  Deep learning in neural networks: An overview , 2014, Neural Networks.

[17]  Hossam Faris,et al.  A Comparison between Regression, Artificial Neural Networks and Support Vector Machines for Predicting Stock Market Index , 2015 .

[18]  Roy Rada,et al.  Dilemmas in knowledge-based evolutionary computation for financial investing , 2013, Intell. Decis. Technol..

[19]  Alexandros Iosifidis,et al.  Using deep learning to detect price change indications in financial markets , 2017, 2017 25th European Signal Processing Conference (EUSIPCO).

[20]  Sung-Bae Cho,et al.  A review and empirical analysis of neural networks based exchange rate prediction , 2018, Intell. Decis. Technol..

[21]  Martin A. Riedmiller,et al.  A direct adaptive method for faster backpropagation learning: the RPROP algorithm , 1993, IEEE International Conference on Neural Networks.

[22]  Geoffrey E. Hinton,et al.  On the importance of initialization and momentum in deep learning , 2013, ICML.

[23]  Sahil Shah,et al.  Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques , 2015, Expert Syst. Appl..

[24]  Jianqiang Li,et al.  WCP-RNN: a novel RNN-based approach for Bio-NER in Chinese EMRs , 2018, The Journal of Supercomputing.