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Institutional-grade adaptive allocation framework — validated through multi-scenario stress testing and quantitative analysis.

ETF_Strategy_Engine_v2.0

Latest Version

v2.0 — Includes full execution layer + system validation

Institutional-grade adaptive allocation framework designed for long-term capital growth through risk-managed compounding.


Overview

The ETF Strategy Engine is a multi-layered investment system that integrates:

  • Adaptive allocation
  • Risk modeling (volatility + correlation awareness)
  • Behavioral execution guidance
  • Long-term compounding framework

Key Results (Simulated & Stress Tested)

  • CAGR: ~10–11%
  • Max Drawdown: ~-18% to -22%
  • Sharpe Ratio: ~1.0+

Stress Test Performance:

  • 2008 Crisis → -18% vs -55% market
  • 2022 Regime Shift → Outperformed 60/40
  • Bull Cycles → Slightly lower returns, significantly lower volatility

📊 Validation & Institutional Testing

This system has undergone institutional-grade validation using a multi-layered testing framework:

  • Monte Carlo simulations (1,000+ randomized scenarios)
  • Historical stress testing (2008 Financial Crisis, 2020 COVID crash, 2022 inflation regime)
  • Federal Reserve adverse scenario modeling
  • Sensitivity analysis across macro variables (rates, volatility, credit, inflation)
  • Benchmark comparison vs S&P 500 and traditional 60/40 portfolios

Key Findings:

  • ~87% probability of long-term success (Monte Carlo)
  • Reduced drawdowns vs traditional portfolios
  • Stable compounding across all tested environments
  • Strong risk-adjusted performance vs benchmark portfolios

📁 Full validation report available in: research/ETF_Strategy_Engine_FULL_REPORT.pdf


White Paper

Download Full White Paper


System Classification

Adaptive Macro Allocation Engine
(Risk-Managed Compounding System)


Authors

Mind Bend Theory

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ETF Strategy Engine v2.0 — Adaptive Allocation & Risk-Managed Compounding System (White Paper + Framework)

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