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An algorithmic trading platform

Project description

hyperdrive: Robinhood analytics and algorithmic trading

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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] Symbols
    • [x] OHLC
    • [x] Intraday
  • [x] Actions

    • [x] Dividends
    • [x] Splits
    • [ ] Mergers
    • [ ] Buybacks
  • [ ] Sentiment

  • [ ] 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

Project details


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