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Stock Market Prediction Using LSTM Recurrent Neural Network - 2020

Stock Market Prediction Using Lstm Recurrent Neural Network

Research Area:  Machine Learning

Abstract:

It has never been easy to invest in a set of assets, the abnormally of financial market does not allow simple models to predict future asset values with higher accuracy. Machine learning, which consist of making computers perform tasks that normally requiring human intelligence is currently the dominant trend in scientific research. This article aims to build a model using Recurrent Neural Networks (RNN) and especially Long-Short Term Memory model (LSTM) to predict future stock market values. The main objective of this paper is to see in which precision a Machine learning algorithm can predict and how much the epochs can improve our model.

Keywords:  

Author(s) Name:  Adil Moghar, Mhamed Hamiche

Journal name:  Procedia Computer Science

Conferrence name:  

Publisher name:  Elsevier

DOI:  10.1016/j.procs.2020.03.049

Volume Information:  Volume 170, 2020, Pages 1168-1173