Mastering PatternExplorer for AmiBroker: A Practical Guide

Mastering PatternExplorer for AmiBroker: A Practical Guide

Overview

A concise, step-by-step manual to using PatternExplorer inside AmiBroker to find, validate, and trade recurring chart patterns and statistical edge. Covers setup, pattern discovery workflow, filtering, backtesting, and practical deployment.

Who it’s for

• Technical traders using AmiBroker
• Quant traders seeking systematic pattern discovery
• Developers building AFL-based pattern screens

Key Sections

1. Installation & Setup

   • Installing PatternExplorer and required AFL libraries.
   • Configuring data sources, timeframes, and database settings.

2. Pattern Discovery Workflow

   • Defining pattern templates and parameter ranges.
   • Running exhaustive scans and using similarity/distance measures.
   • Visualizing pattern clusters and representative examples.

3. Filtering & Feature Engineering

   • Applying quality filters (support, volume, minimum length).
   • Creating derived features (normalized amplitude, slope, duration).
   • Using z-score and percentile transforms for comparability.

4. Backtesting & Robustness Checks

   • Translating discovered patterns into AFL rules.
   • Walk-forward testing and out-of-sample validation.
   • Monte Carlo permutation tests, parameter sensitivity analysis.

5. Strategy Construction

   • Entry/exit rules, position sizing, risk management.
   • Combining pattern signals with trend or volume filters.
   • Portfolio-level considerations and correlation control.

6. Performance Optimization

   • Speeding scans with optimized AFL, batching, and multicore settings.
   • Efficient memory and disk usage for large databases.

7. Case Studies

   • Short example workflows: mean-reversion pattern, breakout pattern.
   • Real-results snapshots: key metrics (win rate, expectancy, max drawdown).

8. AFL Snippets & Tools

   • Ready-to-use AFL for pattern matching, feature extraction, and testing.
   • Scripts for automated report generation and chart annotation.

9. Common Pitfalls & Best Practices

   • Overfitting risks and how to avoid them.
   • Ensuring economic plausibility and trading friction adjustments.

Expected Outcomes

• Ability to discover repeatable chart patterns.
• Robust methods to convert patterns into tradable rules.
• Faster, more reliable scanning and validation in AmiBroker.

Suggested Appendix

• Reference AFL functions and libraries.
• Checklist for live deployment.
• Glossary of pattern discovery terms.