Automating Technical Analysis
Using data analytics of popular trading strategies and indicators, to identify best trading actions based solely on the price action.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Quantitative Notebooks | 233 | 4 years ago | apache-2.0 | Jupyter Notebook | ||||||
| Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy | ||||||||||
| Automating Technical Analysis | 182 | 5 months ago | 5 | mit | Python | |||||
| Using data analytics of popular trading strategies and indicators, to identify best trading actions based solely on the price action. | ||||||||||
| Neural Finance | 49 | 4 years ago | 2 | apache-2.0 | Python | |||||
| Neural Network for HFT-trading [experimental] | ||||||||||
| Bitcoin_analysis | 38 | 3 years ago | n,ull | Jupyter Notebook | ||||||
| Python Bitcoin is widely used cryptocurrency for digital market. It is decentralised that means it is not own by government or any other company.Transactions are simple and easy as it doesn’t belong to any country.Records data are stored in Blockchain.Bitcoin price is variable and it is widely used so it is important to predict the price of it for making any investment.This project focuses on the accurate prediction of cryptocurrencies price using neural networks. We’re implementing a Long Short Term Memory (LSTM) model using keras; it’s a particular type of deep learning model that is well suited to time series data (or any data with temporal/spatial/structural order e.g. movies, sentences, etc.).We have used different activation function for analysing the efficiency of the system.Instead of historical data we are using live streaming data for better accuracy. | ||||||||||
| Algo Trading | 21 | 3 years ago | mit | |||||||
| This is my github repository where I post trading strategies, tutorials and research on quantitative finance with R, C++ and Python. Some of the topics explored include: machine learning, high frequency trading, NLP, technical analysis and more. Hope you enjoy it! | ||||||||||
| Trading_sim | 19 | 5 years ago | 2 | mit | Python | |||||
| 📈📆 Backtest trading strategies concurrently using historical chart data from various financial exchanges. | ||||||||||
| Bitcoin Analysis | 6 | 4 years ago | MATLAB | |||||||
| Compile, analyse, plot cryptocurrency protocols, networks, marketplaces | ||||||||||
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