Range Bound Trading

Implementation

Implementation of range bound trading follows a modular architecture. Configuration files define parameters, strategy modules handle logic, and exchange adapters manage execution.

Configuration Example

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

# Example configuration for Range Bound Trading
strategy:
  name: range-bound-trading
  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 range bound trading includes unit tests for signal logic, integration tests for exchange interaction, and backtests against historical data with realistic slippage modeling.

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.

Production Notes

In production, range bound trading requires monitoring for API rate limits, database connection pooling, log rotation, alert thresholds, and automated restart procedures. Document runbooks for incident response.