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An algorithmic trading platform

Project description

hyperdrive: Robinhood analytics and algorithmic trading

Build Pipeline Dev Pipeline New Release

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

Testing

python -m pytest -s -v test/test_filename -k function_name

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('hyperdrive')
from Algotrader import HyperDrive  # noqa autopep8

drive = HyperDrive()

Features:

  • 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
    • Symbols
    • OHLC
    • Intraday
  • Actions
    • Dividends
    • Splits
  • Sentiment
  • Company / Micro
    • Profile (Sector, # of Employees)
    • Earnings
    • Cash Flow
    • CEO Compensation
  • Government / Macro
    • Unemployment
    • Real GDP
    • US Recession Probabilities
  • Market
    • General Volatility (VIX)
    • Sector Performance

Strategy

  • Buy and Hold
  • Indicator/TA based
  • Portfolio Optimization

Trading

  • Buy and Sell

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