Chandelier Exit

Page 61 of 220 · Algorithm reference notes

Common Issues

Common issues with chandelier exit include look-ahead bias in backtesting, overfitting to historical regimes, inadequate handling of exchange downtime, and insufficient logging for debugging.

Important: Always validate chandelier exit logic on out-of-sample data before live deployment. Paper trading reveals execution issues that backtests miss.

Configuration Example

Configuration for chandelier exit uses YAML or JSON format. Key parameters include timeframes, signal thresholds, position sizing rules, and risk limits.

# Example configuration for Chandelier Exit
strategy:
  name: chandelier-exit
  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.

MetricValueBenchmark
Sharpe Ratio1.851.20
Max Drawdown-12.4%-18.0%
Win Rate58.2%52.0%
Profit Factor1.721.45

Core Concepts

Understanding chandelier exit requires familiarity with market microstructure, order flow dynamics, and execution latency. The following sections detail each component.

Risk Considerations

Risk management for chandelier exit addresses position limits, stop loss placement, correlation exposure, and worst-case drawdown scenarios. Regular monitoring prevents drift from intended behavior.

Important: Always validate chandelier exit logic on out-of-sample data before live deployment. Paper trading reveals execution issues that backtests miss.