Stock Market Prediction using Sequence to Sequence Learning
Introduction
This repo contains the data and implementation for the DSA4199 Honour Project: Stock Market Prediction using Sequence to Sequence Learning
Requirements
- python=3.7.6
- numpy=1.19.2
- pandas=1.2.1
- ta-lib=0.4.19
- scikit-learn=0.23.2
- matplotlib=3.3.2
Files
The models implemented in models.py. The model training can be done by running the 4 jupyter notebook:
- MLP.ipynb
- lstm-gru-rnnmodel.ipynb
- seq2seq.ipynb
- attn-seq2seq.ipynb
The evaluation and trading test results/plots can be recreated by running eval.ipynb and trading.ipynb.