Stock market forecasting using recurrent neural network

........................................................................................................................ ix Chapter 1 ........................................................................................................................

[1]  Jürgen Schmidhuber,et al.  LSTM: A Search Space Odyssey , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[2]  Amir F. Atiya,et al.  Bankruptcy prediction for credit risk using neural networks: A survey and new results , 2001, IEEE Trans. Neural Networks.

[3]  Clément Farabet,et al.  Torch7: A Matlab-like Environment for Machine Learning , 2011, NIPS 2011.

[4]  Michela Becchi,et al.  Poster: Multiple Pairwise Sequence Alignments with the Needleman-Wunsch Algorithm on GPU , 2012, SC Companion.

[5]  F. Treacy,et al.  Credit Risk Rating at Large U , 1998 .

[6]  Algirdas Maknickas,et al.  Investigation of financial market prediction by recurrent neural network , 2011 .

[7]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[8]  Michela Becchi,et al.  Deploying Graph Algorithms on GPUs: An Adaptive Solution , 2013, 2013 IEEE 27th International Symposium on Parallel and Distributed Processing.

[9]  R. Vasantha Kumari,et al.  NEURAL NETWORK TOWARDS BUSINESS FORECASTING , 2012 .

[10]  Lillian Lee,et al.  Learning of Context-Free Languages: A Survey of the Literature , 1996 .

[11]  Ah Chung Tsoi,et al.  Noisy Time Series Prediction using Recurrent Neural Networks and Grammatical Inference , 2001, Machine Learning.

[12]  Alex Graves,et al.  Supervised Sequence Labelling with Recurrent Neural Networks , 2012, Studies in Computational Intelligence.

[13]  Jürgen Schmidhuber,et al.  Learning to forget: continual prediction with LSTM , 1999 .

[14]  Amir F. Atiya,et al.  Introduction to financial forecasting , 1996, Applied Intelligence.

[15]  Ted Briscoe,et al.  Learning Stochastic Categorial Grammars , 1997, CoNLL.

[16]  P J Webros BACKPROPAGATION THROUGH TIME: WHAT IT DOES AND HOW TO DO IT , 1990 .

[17]  Zahid Iqbal,et al.  Efficient Machine Learning Techniques for Stock Market Prediction , 2013 .

[18]  Shuxiang Xu,et al.  A novel approach for determining the optimal number of hidden layer neurons for FNN’s and its application in data mining , 2008 .

[19]  Adam Blum,et al.  Neural Networks in C++: An Object-Oriented Framework for Building Connectionist Systems , 1992 .

[20]  Jürgen Schmidhuber,et al.  LSTM recurrent networks learn simple context-free and context-sensitive languages , 2001, IEEE Trans. Neural Networks.

[21]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[22]  Eduardo Sontag,et al.  Turing computability with neural nets , 1991 .

[23]  Burton G. Malkiel,et al.  Efficient Market Hypothesis , 1991 .

[24]  Yasubumi Sakakibara,et al.  Recent Advances of Grammatical Inference , 1997, Theor. Comput. Sci..

[25]  Geoffrey E. Hinton,et al.  Speech recognition with deep recurrent neural networks , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[26]  Kosa Golic,et al.  Application of a Neural Network Model for Solving Prediction Problems in Business Management , 2013 .

[27]  Michela Becchi,et al.  Nested Parallelism on GPU: Exploring Parallelization Templates for Irregular Loops and Recursive Computations , 2015, 2015 44th International Conference on Parallel Processing.

[28]  H. Guterman,et al.  Knowledge extraction from artificial neural network models , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[29]  Christian Wolf,et al.  Action Classification in Soccer Videos with Long Short-Term Memory Recurrent Neural Networks , 2010, ICANN.

[30]  Alfredo Vellido,et al.  Neural networks in business: a survey of applications (1992–1998) , 1999 .

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