https://github.com/davidcgong/verena

Strategies and basic research for the stock market
https://github.com/davidcgong/verena

quantopian strategies trading

Last synced: 19 days ago
JSON representation

Strategies and basic research for the stock market

• Host: GitHub
• URL: https://github.com/davidcgong/verena
• Owner: davidcgong
• Created: 2018-11-06T10:17:23.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2023-03-24T21:54:59.000Z (over 1 year ago)
• Last Synced: 2024-10-11T13:25:14.258Z (about 1 month ago)
• Topics: quantopian, strategies, trading
• Language: Python
• Homepage:
• Size: 418 KB
• Stars: 1
• Watchers: 1
• Forks: 2
• Open Issues: 7
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Verena

##  1) LSTM 

LSTM built using the Keras Python package to do time-series prediction. Includes SP500 data. My initial attempt at LSTM is the lstm_part_1.py file

### Requirements

Install requirements.txt file to make sure correct versions of libraries are being used.

* Python 3.5.x

* TensorFlow 1.10.0

* Numpy 1.15.0

* Keras 2.2.2

* Matplotlib 2.2.2

Output for stock market multi-dimensional multi-sequential predictions:

![Output for stock market multiple sequential predictions](https://www.altumintelligence.com/assets/time-series-prediction-using-lstm-deep-neural-networks/sp500_multi_2d.png)

## 2) Algorithms

Algorithms can be found in the Algorithms folder, can be run on either Quantopian or Quantconnect