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 |
Risk Considerations
Risk management for arbitrage bot architecture addresses position limits, stop loss placement, correlation exposure, and worst-case drawdown scenarios. Regular monitoring prevents drift from intended behavior.
Testing Approach
Testing arbitrage bot architecture includes unit tests for signal logic, integration tests for exchange interaction, and backtests against historical data with realistic slippage modeling.
Core Concepts
Understanding arbitrage bot architecture requires familiarity with market microstructure, order flow dynamics, and execution latency. The following sections detail each component.
Configuration Example
Configuration for arbitrage bot architecture uses YAML or JSON format. Key parameters include timeframes, signal thresholds, position sizing rules, and risk limits.
# Example configuration for Arbitrage Bot Architecture
strategy:
name: arbitrage-bot-architecture
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