An algorithmic trading platform
|hyperdrive: Robinhood analytics and algorithmic trading|
hyperdrive is a project to obtain stock data, create trading strategies, test against historical data (backtesting), and deploy strategies for algorithmic trading.
You will need Python 3.8+ and a Robinhood account.
Place your credentials in a file named
.env in the project root directory.
Follow this structure:
RH_USERNAME=... RH_PASSWORD=... RH_2FA=... IEXCLOUD=...
To install the necessary packages, run
pip install -r requirements.txt
To make a script, create a new .py file in the
scripts/ dir with the following code:
import sys sys.path.append('src') from Algotrader import HyperDrive # noqa autopep8 drive = HyperDrive()
- [x] Broker authentication
- [ ] Automated data storage
- [ ] Backtesting engine
- [ ] Monte Carlo simulations
- [ ] Plotting and technical analysis
- [ ] Model training
- [ ] Strategy definition (start with buy and hold)
- [ ] Buy and sell functionality
- [ ] Live trading
- [ ] Documentation
Check out the Roadmap for progress ...
Using Robinhood 2FA, we can simply provide our MFA one-time password in the
.env file to login to Robinhood (via
[ ] Price and Volume
[ ] Sentiment
- [ ] News Sentiment
- [ ] Institutional Sentiment
- [ ] Analyst Recommendations
[ ] Company / Micro
- [ ] Profile (Sector, # of Employees)
- [ ] Earnings
- [ ] Cash Flow
- [ ] CEO Compensation
[ ] Government / Macro
- [ ] Unemployment Rate
- [ ] Real GDP
- [ ] US Recession Probabilities
[ ] Market
- [ ] General Volatility (VIX)
- [ ] Sector Performance
Release history Release notifications | RSS feed
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