Apex Quant:
Adaptive Rotation,
Proven Performance
Apex Quant showcases the RAF Strategy, a quantitative, rules-based portfolio rotation model. Built on adaptive technical filters and validated across 15 years of historical and live data, the strategy is designed to capture growth while mitigating drawdowns. This site provides a concise overview of the methodology, performance results, and supporting research.
Quick Statistics
Key Performance metrics from 2010-2025 QuantConnect backtests.​
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CAGR: 36%
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Max Drawdown​: 33%
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Sharpe Ratio: 1.1
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Sortino Ratio: 1.1
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Win Rate: 67%
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Profit-Loss Ratio: 1.77
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Expectancy per Trade: 0.86%
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Annual Standard Deviation: 24%
Strategy Composition
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​RAF Strategy dynamically rotates between growth-oriented assets (e.g., TQQQ, QQQ, BRK-B) and defensive assets (e.g., GLD, TLT, XLU, XLE, XLV, IBIT) depending on market conditions.
How it works
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Adaptive Filters – Adjusts allocations dynamically to align with changing market conditions.
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Portfolio Rotation – Rotates between growth-oriented assets (e.g., TQQQ, QQQ, BRK-B) and defensive assets (e.g., GLD, TLT, XLU, XLE, XLV, IBIT).
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Rules-Based Process – Removes discretion by following a systematic, quantitative framework.
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Validated Approach – Backtested over 15+ years and live-tested on QuantConnect, showing consistency across regimes.
Track on QuantConnect League
Methodology​​
Optimization was performed using 2020–2024 data. Robustness testing included a rolling 3-year parameter jitter from 2010–2019, with results centered around chosen parameters ±10%. This process was designed to confirm stability and consistency across varying market regimes.
Research & Validation
2025 Live Validation
Backtest vs. Live fills show a +0.02 average difference, demonstrating close alignment between research simulations and real trading execution.
