forcepush 1.0.3

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

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
  • 
  • 
  • 
• Actions
  • 
  • 
• Sentiment
  • News Sentiment
  • 
  • Investor Sentiment
  • Analyst Recommendations
• Company / Micro
  • Profile (Sector, # of Employees)
  • Earnings
  • Cash Flow
  • CEO Compensation
• Government / Macro
  • 
  • 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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