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Stock Price Movement Prediction using Attention-Based Neural Network Framework

Journal: International Journal of Science and Research (IJSR) (Vol.7, No. 8)

Publication Date:

Authors : ; ; ; ; ;

Page : 7-9

Keywords : Stock Price Movement; Neural Network; Attention Mechanism; NLP;

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There is a lot of scientific work going on NLP trying to predict the impact of news on a stock price, much of this uses basic features (such as bags-of-words, named entities etc. ), but fails to capture structured entity-relation, and hence lacks accuracy.1. Encoding the information like daily events, meta-stock information and stocks 50 days moving average using LSTM.2. Employing attention mechanism to rate the relevancy of all events for each stock.3. Using non-linear neural network on the weighted events to predict the stock movement. The model achieved an accuracy of around 72 % on test set.

Last modified: 2021-06-28 19:31:15