I Analyzed 500+ Crypto Trades From My Bot — Here Are the 5 Risk Management Rules That Actually Work

After running a crypto trading bot 24/7 for over a month, I've collected enough data to share what actually works for risk management. Not theory — real results from real trades. The Setup I use Freqtrade, an open-source Python framework, trading 15 crypto pairs on Bybit futures. The bot uses a multi-indicator scoring system where each signal gets a confidence score before execution. Current stats: 67.9% win rate across all pairs 2.12 profit factor 1.42% maximum drawdown 15 trading pairs (BTC, ETH, SOL, BNB, and 11 altcoins) Here are the 5 risk management rules that made the biggest difference. Rule 1: Dynamic Position Sizing > Fixed Lot Size Most tutorials tell you to risk 1-2% per trade. That's a start, but it misses the point. What actually works is confidence-based position sizing: def calculate_position_size(confidence_score, base_risk=0.01): if confidence_score >= 8: return base_risk * 1.5 # High confidence = slightly larger elif confidence_score >= 5: return base_risk *