Common Issues
Common issues with freqtrade position sizing include look-ahead bias in backtesting, overfitting to historical regimes, inadequate handling of exchange downtime, and insufficient logging for debugging.
Production Notes
In production, freqtrade position sizing requires monitoring for API rate limits, database connection pooling, log rotation, alert thresholds, and automated restart procedures. Document runbooks for incident response.
Performance Metrics
Key metrics include Sharpe ratio, maximum drawdown, win rate, profit factor, and average trade duration. Compare against baseline strategies and adjust parameters based on out-of-sample results.
| Metric | Value | Benchmark |
|---|---|---|
| Sharpe Ratio | 1.85 | 1.20 |
| Max Drawdown | -12.4% | -18.0% |
| Win Rate | 58.2% | 52.0% |
| Profit Factor | 1.72 | 1.45 |
Code Structure
The code structure separates concerns: data ingestion, signal generation, risk checks, and order submission. This modularity enables testing and reuse across strategies.
# Example configuration for FreqTrade Position Sizing
strategy:
name: freqtrade-position-sizing
timeframe: 5m
indicators:
- rsi
- ema_fast
- ema_slow
entry_conditions:
- rsi_oversold
- ema_crossover_bullish
exit_conditions:
- rsi_overbought
- stop_loss_hit
risk:
max_position_size: 0.02
stop_loss_pct: 0.015
Implementation
Implementation of freqtrade position sizing follows a modular architecture. Configuration files define parameters, strategy modules handle logic, and exchange adapters manage execution.