Short Term Prediction Framework for Moroccan Stock Market Using Artificial Neural Networks-Reference-Cited by-同舟云学术

Short Term Prediction Framework for Moroccan Stock Market Using Artificial Neural Networks

Published:2018-10-24 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 12th International Conference on Intelligent Systems: Theories and Applications
language:
Short-container-title:

Author:

Labiad Badre¹,Berrado Abdelaziz²,Benabbou Loubna³

Affiliation:

1. Equipe MOAD-SCM Mohammadia School of Engineers Mohammed V University, Rabat, Morocco

2. Equipe AMIPS Mohammadia School of Engineers Mohammed V University, Rabat, Morocco

3. Département Sciences de la Gestion, Université du Québec à Rimouski (UQAR), Campus de Lévis, Québec, Canada

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3289402.3289520

Reference28 articles.

1. Andy. 2017. Recurrent neural networks and LSTM tutorial in Python and TensorFlow. (Oct. 2017). http://adventuresinmachinelearning.com/recurrent-neural-networks-lstm-tutorial-tensorflow/ Andy. 2017. Recurrent neural networks and LSTM tutorial in Python and TensorFlow. (Oct. 2017). http://adventuresinmachinelearning.com/recurrent-neural-networks-lstm-tutorial-tensorflow/

2. Hybrid nonlinear adaptive scheme for stock market prediction using feedback FLANN and factor analysis

3. Surveying stock market forecasting techniques – Part II: Soft computing methods

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