crypto-predictive-risk-factors
Unverified ML strategy on Crypto by unravel-finance. BotFinder score 18 out of 100.
Systematic trading strategies (for crypto assets), using alternative (on-chain, sentiment) data.
Source: github
BotFinder analysis pending.
crypto-predictive-risk-factors
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 exchangeoutflows.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.
⚠ No verified equity curve — no track-record source connected.
Drawdown profile
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Verification ledger
How the score has moved
Recalculated at each data collection. Transparency means showing the bad weeks too.
No score history is stored yet — only the current score is shown.
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Alerts on changes: coming soon
Prop-firm compatibility not provided.
Open-source maintainer on GitHub.
Data-completeness & trust index (not a profitability rating)