Aptet Fitness
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"interpretation": {
"scoreMeaning": "The effective fit score after applying the conservative confidence penalty. Lower confidence reduces the effective fit score but does not, by itself, imply evidence of poor fit.",
"fitScopeMeaning": "Aptet fit is currently universe-conditioned: activation history and fit depend on the other members in the tested cross-sectional universe.",
"rawScoreMeaning": "The unadjusted Aptet-family fit estimate before applying the conservative confidence penalty.",
"activationMeaning": "Activation count measures how often the Aptet ranking would have selected the stock while risk-on.",
"confidenceMeaning": "Reflects the amount and breadth of historical evidence supporting the family-fit score.",
"algorithmFitMeaning": "Measures how consistently this stock works across the Aptet strategy family within this tested universe, not only under its single best parameter combination.",
"comboQualityMeaning": "Fixed-scale normalized profile quality derived from fitnessScore using sigmoid((fitnessScore - 0.35) / 0.22).",
"fitnessScoreMeaning": "Per-profile raw score used for diagnostics and ranking. Higher is better, but it is not the stock's overall Aptet-family fit.",
"forwardReturnMeaning": "Forward returns are measured from the close before activation through each requested horizon.",
"profileBreadthMeaning": "Measures how much of the tested Aptet parameter grid clears a robust quality threshold after weighting for sample confidence.",
"parameterStabilityMeaning": "Measures whether nearby Aptet parameter combinations retain a large share of the best profile's normalized quality.",
"confidenceAdjustmentMeaning": "The current conservative_penalty adjustment retains the existing formula: rawScore * confidence + rawScore * (1 - confidence) * 0.50."
},
"lookbackSummary": [
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"strategyOptions": {
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"blended": "Recommended. Mixes activation quality, activation frequency, return lift, and shadow performance.",
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},
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}Force Fitness
{
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"hitRateLift1D": -0.025434782608695694,
"portfolioSize": 2,
"activationRate": 0.20380434782608695,
"activationCount": 75,
"baselineHitRates": {
"1": 0.5054347826086957,
"5": 0.46153846153846156,
"10": 0.5097493036211699
},
"sampleConfidence": 0.9964444444444445,
"shadowSharpeLike": -0.54539880502834,
"avgForwardReturns": {
"1": -0.0010362804943901442,
"5": -0.005492436923802252,
"10": -0.0026120293236382274
},
"shadowMaxDrawdown": -0.18134355663919688,
"shadowTotalReturn": -0.100247714212923,
"avgForwardReturn1D": -0.0010362804943901442,
"riskOffActivations": 0,
"activationDatesSample": [
"2025-02-04",
"2025-02-05",
"2025-02-06",
"2025-02-07",
"2025-02-10",
"2025-06-13",
"2025-06-16",
"2025-06-17",
"2025-07-02",
"2025-08-14"
],
"horizonObservationCounts": {
"1": 75,
"5": 74,
"10": 72
},
"baselineAvgForwardReturns": {
"1": 0.00009070098018052885,
"5": -0.00014392888891954066,
"10": 0.0004972227475349512
}
}
],
"interpretation": {
"scoreMeaning": "The effective fit score after applying the conservative confidence penalty.",
"backendMeaning": "This Force evaluator uses the alpha1 backend logic that powers the current Force preview path.",
"fitScopeMeaning": "Force fit is currently universe-conditioned because the stock competes against the tested Force universe at each ranking step.",
"rawScoreMeaning": "The unadjusted Force-family fit estimate before the conservative confidence penalty.",
"algorithmFitMeaning": "Measures how consistently this stock works across the Force strategy family within this tested universe.",
"confidenceAdjustmentMeaning": "The current conservative_penalty adjustment retains the existing formula used by the shared family-fit core."
},
"lookbackSummary": [
{
"comboQuality": 0.15858855747914966,
"fitnessScore": -0.01712887439598701,
"lookbackDays": 14,
"returnLift1D": -0.0003400284871379356,
"activationRate": 0.32,
"activationCount": 120,
"sampleConfidence": 0.9977777777777779,
"bestPortfolioSize": 4,
"shadowTotalReturn": -0.07229465349193531,
"avgForwardReturn1D": -0.000316359314495727
},
{
"comboQuality": 0.4272568280718672,
"fitnessScore": 0.28552853879341483,
"lookbackDays": 21,
"returnLift1D": 0.0008477892653639701,
"activationRate": 0.34782608695652173,
"activationCount": 128,
"sampleConfidence": 0.9947916666666667,
"bestPortfolioSize": 4,
"shadowTotalReturn": 0.09044187900968548,
"avgForwardReturn1D": 0.000938490245544499
},
{
"comboQuality": 0.3064967805744481,
"fitnessScore": 0.1703593012801615,
"lookbackDays": 30,
"returnLift1D": 4.3975610023708114e-7,
"activationRate": 0.30362116991643456,
"activationCount": 109,
"sampleConfidence": 1,
"bestPortfolioSize": 3,
"shadowTotalReturn": 0.017502919679354134,
"avgForwardReturn1D": 0.0003657546727915895
},
{
"comboQuality": 0.3476898463558032,
"fitnessScore": 0.2115739521700225,
"lookbackDays": 45,
"returnLift1D": 0.00017233558653988667,
"activationRate": 0.2936046511627907,
"activationCount": 101,
"sampleConfidence": 0.9914191419141914,
"bestPortfolioSize": 3,
"shadowTotalReturn": 0.05959083465070125,
"avgForwardReturn1D": 0.000833495466190243
},
{
"comboQuality": 0.2177985734803012,
"fitnessScore": 0.06872084244563292,
"lookbackDays": 63,
"returnLift1D": -0.0008105391679694917,
"activationRate": 0.17791411042944785,
"activationCount": 58,
"sampleConfidence": 1,
"bestPortfolioSize": 2,
"shadowTotalReturn": 0.0006159780397738679,
"avgForwardReturn1D": 0.000194615392270725
}
],
"strategyOptions": {
"shadow": "Scores the stock like a standalone trade-only-when-active strategy.",
"blended": "Recommended. Mixes activation quality, activation frequency, return lift, and shadow performance.",
"coverage": "Rewards stocks that activate often without giving up too much quality.",
"precision": "Prioritizes hit rate and average return after activation."
},
"backendAlgorithm": "alpha1",
"universeIdentity": {
"hash": "f51d34368f255ad76d8db96bd46fc3d0d1897a841d2d035b2684520a7829cbf5",
"size": 13,
"members": [
"A",
"SMH",
"XLB",
"XLC",
"XLE",
"XLF",
"XLI",
"XLK",
"XLP",
"XLRE",
"XLU",
"XLV",
"XLY"
],
"version": 1
},
"scoreModeDescription": "Recommended. Mixes activation quality, activation frequency, return lift, and shadow performance."
}
TM