HPE HMA–Alligator Strategy (2019-2026) Walk-Forward Optimized + Monte Carlo Validated Trading System
📈 HPE HMA–Alligator StrategyWalk-Forward Optimized & Monte Carlo Validated Trading SystemThe HPE HMA–Alligator Strategy is a fully systematic trading framework built for Hewlett Packard Enterprise (HPE). It combines momentum acceleration and structural trend logic, then validates performance using professional-grade robustness testing.This is not a simple backtest — it is: ✅ Walk-Forward Optimized ✅ Out-of-Sample Tested ✅ Monte Carlo Stress Tested ✅ Fee & Slippage Adjusted ✅ Fully Reproducible Python Code 🔍 Strategy ConceptThe system merges two powerful concepts:1️⃣ Momentum Acceleration (Hull Moving Average – HMA) Detects changes in momentum speed Identifies early structural shifts Reduces lag compared to traditional moving averages 2️⃣ Trend Structure (Alligator Indicator) Uses Jaw / Teeth / Lips alignment Exits when structure weakens Filters false momentum signals Entries and exits are shifted by 1 bar for realistic execution and use the next candle open price.🧠 Walk-Forward Optimization (WFO)Instead of fitting one parameter set over the entire dataset, this strategy uses: 4-Year Training Window 1-Year Testing Window Rolling Forward Re-Optimization Parameter Grid Search Best Parameters Selected per Period This ensures the strategy adapts to changing market regimes and reduces overfitting risk.📊 Out-of-Sample Performance (2019–2026)Execution: DailyFees: 0.1%Slippage: 0.2%📈 Performance Summary Total Return: 104.87% Benchmark Return: 102.82% Max Drawdown: 55.79% Sharpe Ratio: 0.55 Sortino Ratio: 0.79 Profit Factor: 1.56 Win Rate: 56.41% Total Trades: 40 Best Trade: +78.50% Worst Trade: -37.08% Interpretation Slightly outperformed Buy & Hold Positive expectancy Profitable with moderate trade frequency Drawdowns are significant but statistically consistent with trend systems 🔬 Monte Carlo Robustness TestingTo measure statistical reliability: 1,000 Block Bootstrap Simulations Block size = 5 days Reconstructed equity curves Distribution analysis of returns and drawdowns 📊 Monte Carlo ResultsTotal Return Distribution Median: 122.25% 5th Percentile: -58.03% 95th Percentile: 876.51% Max Drawdown Distribution Median: -58.06% 5th Percentile: -81.49% 95th Percentile: -39.27% What This Means Strategy has strong upside skew Volatility is normal for momentum systems Deep drawdowns are statistically expected System remains profitable across wide simulation paths 🧩 What You Get Original Parameter Version 2026 Optimized Parameter Version Full Walk-Forward Engine Monte Carlo Simulation Framework Performance Charts Portfolio Statistics Buy & Hold Comparison Fully Commented Python Code 🎯 Who This Is For Quantitative traders Strategy developers Algorithmic traders Systematic investors Researchers testing robustness techniques ⚠️ Risk DisclosureThis system experiences: High volatility Deep drawdowns Regime-dependent performance It is designed for disciplined capital management and risk-controlled deployment.Past performance does not guarantee future results.
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