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 Log Rotation Configuration
strategy:
name: log-rotation-configuration
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
Testing Approach
Testing log rotation configuration includes unit tests for signal logic, integration tests for exchange interaction, and backtests against historical data with realistic slippage modeling.
Configuration Example
Configuration for log rotation configuration uses YAML or JSON format. Key parameters include timeframes, signal thresholds, position sizing rules, and risk limits.
# Example configuration for Log Rotation Configuration
strategy:
name: log-rotation-configuration
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
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 |
Implementation
Implementation of log rotation configuration follows a modular architecture. Configuration files define parameters, strategy modules handle logic, and exchange adapters manage execution.