Quant Research Desk
Independent research on markets, models, backtests, and applied AI.
Long-form notes, empirical tests, and implementation memos for readers who prefer transparent assumptions over market commentary.
Research
Quantitative research notes on markets, factors, risk, and systematic strategies — ordered by publication date.
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PBands Lower Band Mean Reversion Long Only — Backtesting Analysis
PBands Lower Band Mean Reversion Long Only — Backtesting Analysis Backtest period: 2016-01-01 to 2020-01-01 | Universe: XLP | Engine: quantstrat (R) — Strategy Overview My hypothesis was that consumer…
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XLF Sector Allocation Strategy Should Prioritize Risk-Controlled Exposure Over Daily Timing
Executive Summary Return profile: XLF earned 19.46% annualized with 15.22% volatility and a 16.61% maximum drawdown in the sample. Statistical edge: Weak. Variance-ratio tests do not reject a random-walk benchmark,…
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SPY Shows Strong Returns But No Reliable Daily Timing Edge; Focus on Volatility and Risk Management
Executive Summary Return profile: SPY earned 23.94% annualized with 12.81% volatility and a 10.15% maximum drawdown in the sample. Statistical edge: Weak. Variance-ratio tests do not reject a random-walk benchmark,…
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NVDA’s 114% Annualized Return Shows No Reliable Daily Timing Edge: A Risk-Aware Allocation Hypothesis
Executive Summary Return profile: NVDA earned 114.11% annualized with 49.53% volatility and a 29.46% maximum drawdown in the sample. Statistical edge: Weak. Variance-ratio tests do not reject a random-walk benchmark,…
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XLP Shows Defensive Potential With Limited Daily Return Predictability, Favoring Risk-Managed Strategies
Executive Summary Return profile: XLP earned 6.03% annualized with 10.61% volatility and a 13.57% maximum drawdown in the sample. Statistical edge: Weak. Variance-ratio tests do not reject a random-walk benchmark,…
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