molson194 / LSTM-Stock-PredictionLinks
Day-Trading algorithm using LSTM to predict intraday stock movement
☆20Updated 6 years ago
Alternatives and similar repositories for LSTM-Stock-Prediction
Users that are interested in LSTM-Stock-Prediction are comparing it to the libraries listed below
Sorting:
- Having effective intraday forecast for the level of trading volume is of vital importance to algorithmic trading and portfolio management…☆50Updated 5 years ago
- trading strategy is a fixed plan to go long or short in markets, there are two common trading strategies: the momentum strategy and the …☆60Updated 5 years ago
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆67Updated 2 years ago
- Trend Prediction for High Frequency Trading☆43Updated 2 years ago
- Intraday momentum strategy that buys (sells) leveraged ETFs late in the trading session following a significant intraday gain (loss) and …☆26Updated last year
- Implementation of algorithmic trading using reinforcement learning.☆29Updated 5 years ago
- Deep Q-Learning Applied to Algorithmic Trading☆28Updated 3 months ago
- Scalping day trading strategy☆43Updated 5 years ago
- Artificial Intelligence for Trading☆65Updated 2 years ago
- Cryptocurrency Trading with Reinforcement Learning based on Backtrader☆44Updated 8 months ago
- A python script that estimates the support and resistance lines of a stock's prices over a time period☆76Updated 4 years ago
- ☆75Updated last year
- ☆11Updated 4 years ago
- ☆29Updated 2 years ago
- stock-pairs-trading is a python library for backtest with stock pairs trading using kalman filter on Python 3.8 and above.☆38Updated last year
- Predicting Profitable Day Trading Positions using Decision Tree Classifiers. scikit-learn | Flask | SQLite3 | pandas | MLflow | Heroku | …☆57Updated 3 years ago
- LSTM stock prediction and backtesting☆14Updated 5 years ago
- In this work, the application of the Triple-Barrier Method and Meta-Labeling techniques are explored using XGBoost to develop a sentiment…☆22Updated last year
- In this project, I had backtested the cross-over trading strategy on Google Stock from Jan 2016 to June 2020. By using historical time-se…☆44Updated 5 years ago
- High Frequency Jump Prediction Project☆39Updated 5 years ago
- ☆46Updated 3 years ago
- This project is part of my internship at ULiege on Deep RL in stock market trading☆44Updated last year
- Uisng CNN to predicte stock market trend, and feeding with 2D images☆15Updated 7 years ago
- These are trading results and arbitrage models from Southern China Center for Statistical Science (SC2S2), Sun Yat-sen University☆20Updated 6 years ago
- Tools to calculate and plot support/resistance lines for OHLC datasets☆26Updated 7 years ago
- Capital Asset Pricing Model implementation in python to analyze stock risk and return.☆26Updated 3 years ago
- Stock Price prediction using news data. The datasets used consists news and stock price data from 2008 to 2016. The polarity(Subjectivity…☆48Updated 7 years ago
- Find trading pairs with Machine Learning☆41Updated 4 years ago
- High Frequency Pairs Trading Based on Statistical Arbitrage (Python)☆105Updated 6 years ago
- Deep q learning on determining buy/sell signal and placing orders☆50Updated 6 years ago