Hull Moving Average

Page 63 of 220 · Automation notes archive

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

Risk Considerations

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

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

Overview

This guide covers hull moving average implementation in automated trading systems. The approach combines established patterns with operational considerations drawn from production deployments.

Common Issues

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

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

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 Hull Moving Average
strategy:
  name: hull-moving-average
  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