{"repo":"unravel-finance/crypto-predictive-risk-factors","free":true,"listed":false,"github":"https://github.com/unravel-finance/crypto-predictive-risk-factors","clone":"git clone https://github.com/unravel-finance/crypto-predictive-risk-factors.git","description":"Systematic trading strategies (for crypto assets), using alternative (on-chain, sentiment) data.","language":"Python","stars":18,"topics":["cryptocurrency","systematic-trading-strategies","trading","trading-algorithm","trading-algorithms","trading-strategies"],"license":"MIT","category":"trading","readme_excerpt":"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 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.","default_branch":null,"files":null,"tree":[],"storefront":"/r/unravel-finance","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/unravel-finance/crypto-predictive-risk-factors/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}