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.",
"coverage": "Rewards stocks that activate often without giving up too much quality.",
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},
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"version": 1
},
"scoreModeDescription": "Recommended. Mixes activation quality, activation frequency, return lift, and shadow performance."
}Force Fitness
{
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"2025-03-12",
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"horizonObservationCounts": {
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"10": 181
},
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},
{
"topN": 5,
"ticker": "HII",
"hitRates": {
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"10": 0.6629834254143646
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"hitRate1D": 0.5359116022099447,
"rankWeights": [
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0.20000000000000004,
0.10000000000000002
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"returnLift1D": -0.000982572629688487,
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"2025-03-13",
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"horizonObservationCounts": {
"1": 181,
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],
"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": [
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"returnLift1D": 0.0014999692305805042,
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"activationCount": 142,
"sampleConfidence": 1,
"bestPortfolioSize": 3,
"shadowTotalReturn": 0.41580733891231714,
"avgForwardReturn1D": 0.0027924625799748163
},
{
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"lookbackDays": 21,
"returnLift1D": 0.0006081566505584867,
"activationRate": 0.4266304347826087,
"activationCount": 157,
"sampleConfidence": 1,
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"shadowTotalReturn": 0.3034645251408292,
"avgForwardReturn1D": 0.0020255577085945783
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{
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"lookbackDays": 30,
"returnLift1D": 0.0007972036000595607,
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"sampleConfidence": 1,
"bestPortfolioSize": 4,
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{
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"lookbackDays": 45,
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{
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"lookbackDays": 63,
"returnLift1D": 0.0009170106034207012,
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"shadowTotalReturn": 0.678971501054628,
"avgForwardReturn1D": 0.0023431145658789837
}
],
"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": "8e62532831ecdea2208bda5a49729e782d709c2590d05eca55354652112077bf",
"size": 13,
"members": [
"HII",
"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