Maximum Adverse Excursion

Configuration Example

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

# Example configuration for Maximum Adverse Excursion
strategy:
  name: maximum-adverse-excursion
  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 maximum adverse excursion includes unit tests for signal logic, integration tests for exchange interaction, and backtests against historical data with realistic slippage modeling.

Implementation

Implementation of maximum adverse excursion follows a modular architecture. Configuration files define parameters, strategy modules handle logic, and exchange adapters manage execution.

Risk Considerations

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

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 Maximum Adverse Excursion
strategy:
  name: maximum-adverse-excursion
  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