Effectiveness of Deep Learning Long Short-Term Memory Network for Stock Price Prediction on Graphics Processing Unit
Author:
Affiliation:
1. American University of Nigeria,School of Information Technology & Computing,Nigeria
2. Al-Hikmah University,Department of Business Administration,Ilorin,Nigeria
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9764877/9764959/09765181.pdf?arnumber=9765181
Reference46 articles.
1. Stock market trading rule discovery using technical charting heuristics
2. Financial Market Time Series Prediction with Recurrent Neural Networks;bernal,2012
3. Evaluating multiple classifiers for stock price direction prediction
4. Forecasting financial time series using a low complexity recurrent neural network and evolutionary learning approach
5. Comparison of direct and iterative artificial neural network forecast approaches in multi-periodic time series forecasting
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