Active Risk Overlays for Crypto Assets with Predictive Exogenous Risk Factors

A collection of strategies, backtesting tools, focusing on turning alternative / on-chain data into predictive risk factors to manage portfolio volatility.

It's intended as a sample repository, containing:

• Vectorized backtesting function for efficient strategy testing
• Basic Transaction cost modeling
• Performance metrics calculation

Installation

pip install -r requirements.txt

Usage

Exchange Outflow Risk Overlay

The exchange_outflows.py script demonstrates how to turn exchange outflow data into an effective active risk overlay on top of Bitcoin:

• High outflows might indicate infestor confidence, and reduce the assets available for immediate selling
• Low outflows might indicate that crypto assets on exchanges are pilingup

API Integration

The repository uses:

• Unravel Core API to access Predictive Risk Factors. Sign up for live access at unravel. Trial API Key included, that provides weekly data for 2022-2024.
• Binance API for price data

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.