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        0.00374991549716188,
        0.0013752256018924787,
        0.006471621290184984,
        0.00920261250727855
      ],
      "spy": [
        0.017424615282435912,
        0.008305375388603134,
        -0.023244102547507927,
        -0.018370732806505304,
        -0.07467284781452077,
        0.019801456311220798,
        -0.0064377281142873445
      ]
    }
  },
  "tools": [
    {
      "id": "strategy_report",
      "title": "Strategy report",
      "href": "../strategies/tactical-permanent-portfolio.html",
      "status": "ok",
      "note": "Equity, allocations, and replication metrics."
    },
    {
      "id": "quantstats",
      "title": "QuantStats tearsheet",
      "href": "../tearsheets/strategies/tactical-permanent-portfolio.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": "Tactical Permanent Portfolio receives a research grade of F (composite 41 / 100) on Paper-to-Profit robustness tests run against published monthly ours versus SPY. On these tests the published path does not currently support a constructive allocation case.",
    "edge": "The path makes money vs zero (p=0.000) but is not a significant edge versus SPY (p=0.082, excess -0.36% per month). Same failure mode as a strategy that only rides beta.",
    "bootstrap": "Block bootstrap of consecutive months (400 paths): P(beat SPY) over 6.0 months is 30%; over 24.0 months is 22%. This is the Paper-to-Profit 'realistic path' test, not a reshuffled iid sample.",
    "persistence": "15% of 12-month OLS windows have a significantly positive slope and 58% are significantly negative. Terminal strategy/SPY wealth ratio is 0.33. 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 0.73; second/first-half Sharpe ratio is 0.82. 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 1.037%. 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 19% of classified months (4.0/7.0 regimes). In bear/strong-bear/vol-down months it beats SPY 100% of the time. Crisis windows: Dot-com bust: strategy 32.1% vs SPY -38.4%; Global Financial Crisis: strategy 14.9% vs SPY -46.0%; COVID crash: strategy 2.0% vs SPY -19.4%; 2022 inflation shock: strategy -7.6% vs SPY -23.9%.",
    "headline": "Published CAGR 8.10% / Sharpe 1.27 / max DD -10.5% over 669 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": 23.762376237623762,
    "sharpe": 89.60396039603961,
    "score": 27.722772277227723
  },
  "generated_at": "2026-09-22T18:23:05Z"
}