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      ],
      "sharpe": [
        1.2030652797656718,
        1.2017098562850286,
        1.2003544328043854,
        1.1989990093237424,
        1.1976435858430992,
        1.196288162362456,
        1.194932738881813,
        1.19357731540117,
        1.1922218919205267,
        1.1908664684398838,
        1.1895110449592403,
        1.1881556214785973,
        1.1868001979979543,
        1.1854447745173111,
        1.184089351036668,
        1.1827339275560251,
        1.1813785040753817,
        1.1800230805947385,
        1.1786676571140955,
        1.1773122336334525,
        1.1759568101528093,
        1.1746013866721663,
        1.173245963191523,
        1.1718905397108799,
        1.1705351162302369
      ],
      "cagr": [
        0.07910725640915528,
        0.07901241585316754,
        0.07891758293772178,
        0.07882275766225955,
        0.07872794002621886,
        0.07863313002904393,
        0.07853832767017388,
        0.07844353294904893,
        0.07834874586510954,
        0.07825396641779703,
        0.07815919460654985,
        0.0780644304308118,
        0.07796967389002285,
        0.07787492498362347,
        0.07778018371105455,
        0.07768545007175609,
        0.07759072406516831,
        0.07749600569073567,
        0.07740129494789638,
        0.07730659183609268,
        0.07721189635476522,
        0.07711720850335446,
        0.0770225282813004,
        0.07692785568804772,
        0.07683319072303552
      ]
    },
    "noise": {
      "labels": [
        "0.05",
        "0.1",
        "0.2",
        "0.3",
        "0.5",
        "0.75",
        "1.0",
        "1.5"
      ],
      "median_sharpe": [
        1.2015932183349478,
        1.1972092455656456,
        1.1801412640990354,
        1.1532480769465578,
        1.0781399940876566,
        0.965817964089257,
        0.8548359116844702,
        0.6718503457793107
      ],
      "p10_sharpe": [
        1.2011515999057307,
        1.1954524353056377,
        1.1732640593990447,
        1.1383029161008238,
        1.040662408384252,
        0.8946437693863326,
        0.7503671012601096,
        0.5124858655834024
      ],
      "p90_sharpe": [
        1.202034836764165,
        1.1989660558256534,
        1.1870184687990262,
        1.168193237792292,
        1.1156175797910612,
        1.0369921587921813,
        0.9593047221088307,
        0.831214825975219
      ]
    },
    "regimes": {
      "labels": [
        "Strong bull",
        "Bull",
        "Sideways",
        "Bear",
        "Strong bear",
        "Volatility up",
        "Volatility down"
      ],
      "strategy": [
        0.007926940793470017,
        0.006898571393663614,
        -0.005502667929646495,
        -0.0012039172534875934,
        -0.007933743266476298,
        0.007519510665172199,
        0.004548894929140894
      ],
      "spy": [
        0.017424615282435912,
        0.008305375388603134,
        -0.023244102547507927,
        -0.018370732806505304,
        -0.07467284781452077,
        0.019801456311220798,
        -0.0064377281142873445
      ]
    }
  },
  "tools": [
    {
      "id": "strategy_report",
      "title": "Strategy report",
      "href": "../strategies/gtaa-13.html",
      "status": "ok",
      "note": "Equity, allocations, and replication metrics."
    },
    {
      "id": "quantstats",
      "title": "QuantStats tearsheet",
      "href": "../tearsheets/strategies/gtaa-13.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": "Faber's Global Tactical Asset Alloc. 13 receives a research grade of F (composite 45 / 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=0.112, excess -0.30% 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 37%; over 24.0 months is 38%. This is the Paper-to-Profit 'realistic path' test, not a reshuffled iid sample.",
    "persistence": "21% of 12-month OLS windows have a significantly positive slope and 48% are significantly negative. Terminal strategy/SPY wealth ratio is 0.41. 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 0.85; second/first-half Sharpe ratio is 0.69. 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 0.351%. 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 12.1% vs SPY -38.4%; Global Financial Crisis: strategy -4.9% vs SPY -46.0%; COVID crash: strategy -4.5% vs SPY -19.4%; 2022 inflation shock: strategy -4.1% vs SPY -23.9%.",
    "headline": "Published CAGR 7.91% / Sharpe 1.20 / max DD -12.1% over 426 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": 22.277227722772277,
    "sharpe": 82.67326732673267,
    "score": 45.04950495049505
  },
  "generated_at": "2026-09-22T18:23:05Z"
}