hyperdrive 0.42.0

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.

Getting Started

Prerequisites

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=...

Installation

To install the necessary packages, run

pip install -r requirements.txt

Use

Making Scripts

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()

Features:

• [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 ...

Auth

Using Robinhood 2FA, we can simply provide our MFA one-time password in the .env file to login to Robinhood (via pyotp).

Data

• [ ] Price and Volume

  • [x]
  • [x]
  • [x]

• [x] Actions

  • [x]
  • [x]
  • [ ] Mergers
  • [ ] Buybacks

• [ ] Sentiment

  • [ ] News Sentiment
  • [x]
  • [ ] 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

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