Investigation Into The Effectiveness Of Long Short Term Memory Networks For Stock Price Prediction
arXiv:1603.07893v363 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental study applying existing LSTM methods to stock price prediction, with no clear problem statement for a specific audience.
The paper investigated the effectiveness of Long Short-Term Memory (LSTM) networks for stock price prediction, exploring various architectures trained and tested using backpropagation through time.
The effectiveness of long short term memory networks trained by backpropagation through time for stock price prediction is explored in this paper. A range of different architecture LSTM networks are constructed trained and tested.