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        0.6449489202525485,
        0.439105749467961
      ],
      "p90_sharpe": [
        1.038586215680078,
        1.035896978511929,
        1.0254310410223635,
        1.0089530510774198,
        0.9630120429584796,
        0.8945117600004879,
        0.8270444842700508,
        0.7162058538475807
      ]
    },
    "regimes": {
      "labels": [
        "Strong bull",
        "Bull",
        "Sideways",
        "Bear",
        "Strong bear",
        "Volatility up",
        "Volatility down"
      ],
      "strategy": [
        0.02192328493335818,
        0.010339648575227602,
        -0.028863011919862226,
        -0.019972396102070526,
        null,
        0.02939344573407236,
        0.01390412792199637
      ],
      "spy": [
        0.013943287336567353,
        0.0097168992812941,
        -0.028492105700941038,
        -0.018370732806505304,
        null,
        0.022367980213247252,
        -0.004379357379830185
      ]
    }
  },
  "tools": [
    {
      "id": "strategy_report",
      "title": "Strategy report",
      "href": "../strategies/tqqq-quadrant-stack.html",
      "status": "ok",
      "note": "Equity, allocations, and replication metrics."
    },
    {
      "id": "quantstats",
      "title": "QuantStats tearsheet",
      "href": "../tearsheets/strategies/tqqq-quadrant-stack.html",
      "status": "ok",
      "note": "Full QuantStats HTML from the same monthly ours path."
    },
    {
      "id": "paper_to_profit",
      "title": "Paper to Profit robustness",
      "href": "https://papertoprofit.substack.com/t/tutorials",
      "status": "ok",
      "note": "t-test vs zero and SPY, overlapping-block bootstrap, rolling OLS alpha decay, 70/30 stability, extra-bps cost grid, return-space noise, and seven SPY regimes. Walk-forward parameter search is not estimable on this catalog snapshot."
    }
  ],
  "writeup": {
    "verdict": "TQQQ Quadrant Stack receives a research grade of A (composite 85 / 100) on Paper-to-Profit robustness tests run against published monthly ours versus SPY. The statistical edge and stress tests are strong enough to keep as a candidate; this is still a historical scorecard, not a forecast.",
    "edge": "Monthly mean is 1.56%. t-test vs zero p=0.000; vs SPY p=0.001 (excess 0.71% per month). The path is statistically distinct from SPY on this window.",
    "bootstrap": "Block bootstrap of consecutive months (400 paths): P(beat SPY) over 6.0 months is 72%; over 24.0 months is 82%. This is the Paper-to-Profit 'realistic path' test, not a reshuffled iid sample.",
    "persistence": "61% of 12-month OLS windows have a significantly positive slope and 15% are significantly negative. Terminal strategy/SPY wealth ratio is 7.39. A steadily rising log-relative-wealth line is the decay test from the tutorial; a late collapse is a warning.",
    "stability": "70/30 OOS/IS Sharpe ratio is 0.97; second/first-half Sharpe ratio is 0.90. Walk-forward parameter search is not estimable on a frozen catalog snapshot; this split is the overfit proxy. Return-space noise did not halve Sharpe on the tested grid.",
    "cost": "Average daily turnover is 0.320%. Additional one-way costs through 24 bps did not cut Sharpe in half. That is the tutorial's cost-robust case.",
    "regimes": "The path beats SPY in 93% of classified months (4.0/6.0 regimes). In bear/strong-bear/vol-down months it beats SPY 79% of the time. Crisis windows: Dot-com bust: strategy -3.8% vs SPY -31.4%; Global Financial Crisis: strategy -12.4% vs SPY -46.0%; COVID crash: strategy -12.5% vs SPY -19.4%; 2022 inflation shock: strategy -26.5% vs SPY -23.9%.",
    "headline": "Published CAGR 18.57% / Sharpe 1.04 / max DD -30.4% over 300 months. Those headline stats are context only; the grade is the robustness tests above.",
    "limitations": "Tests use published monthly ours, already lagged one bar in the engine, versus SPY. t-tests assume roughly comparable monthly means; Wilcoxon is shown as a non-normal check. Bootstrap paths are overlapping consecutive months (not iid reshuffles). Noise is added to monthly returns, not to OHLC, because this producer does not rerun backtests. Walk-forward parameter optimization, SPA, and PBO are not estimable without a trial ledger. Fee drag is extra one-way bps on catalog average daily turnover, on top of the published costed path."
  },
  "ranks": {
    "cagr": 96.03960396039604,
    "sharpe": 46.53465346534654,
    "score": 99.00990099009901
  },
  "generated_at": "2026-09-22T18:23:05Z"
}