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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"version": 1
},
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}Force Fitness
{
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"rankWeights": [
0.4000000000000001,
0.30000000000000004
],
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"eligibleDays": 344,
"fitnessScore": -0.2763142240219744,
"lookbackDays": 45,
"returnLift1D": -0.0037104927861652355,
"hitRateLift1D": 0.0032411120021384465,
"portfolioSize": 2,
"activationRate": 0.5058139534883721,
"activationCount": 174,
"baselineHitRates": {
"1": 0.4680232558139535,
"5": 0.5088235294117647,
"10": 0.5164179104477612
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"sampleConfidence": 0.999616858237548,
"shadowSharpeLike": 0.26397876658695585,
"avgForwardReturns": {
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"5": 0.0149079829228692,
"10": 0.022024940723967375
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"shadowMaxDrawdown": -0.7199986620826178,
"shadowTotalReturn": -0.19215050496756025,
"avgForwardReturn1D": 0.0018635540488477148,
"riskOffActivations": 0,
"activationDatesSample": [
"2025-06-16",
"2025-06-18",
"2025-06-20",
"2025-06-23",
"2025-06-24",
"2025-06-25",
"2025-06-26",
"2025-06-27",
"2025-06-30",
"2025-07-01"
],
"horizonObservationCounts": {
"1": 174,
"5": 174,
"10": 173
},
"baselineAvgForwardReturns": {
"1": 0.00557404683501295,
"5": 0.02856110821429323,
"10": 0.05870852089383496
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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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"fitnessScore": 2.2073050187004517,
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"returnLift1D": 0.007310897211830267,
"activationRate": 0.4053333333333333,
"activationCount": 152,
"sampleConfidence": 1,
"bestPortfolioSize": 2,
"shadowTotalReturn": 1.898551008488249,
"avgForwardReturn1D": 0.010446612630216906
},
{
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"fitnessScore": 0.937352886475408,
"lookbackDays": 21,
"returnLift1D": 0.004012776886023142,
"activationRate": 0.43478260869565216,
"activationCount": 160,
"sampleConfidence": 1,
"bestPortfolioSize": 4,
"shadowTotalReturn": 0.7545862464125701,
"avgForwardReturn1D": 0.007447549075520374
},
{
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"fitnessScore": 1.253481345924402,
"lookbackDays": 30,
"returnLift1D": 0.0027233409721488496,
"activationRate": 0.48467966573816157,
"activationCount": 174,
"sampleConfidence": 1,
"bestPortfolioSize": 4,
"shadowTotalReturn": 1.0173223253691197,
"avgForwardReturn1D": 0.0076243584864643475
},
{
"comboQuality": 0.804314582248873,
"fitnessScore": 0.6609660632672394,
"lookbackDays": 45,
"returnLift1D": 0.0002164229798870057,
"activationRate": 0.5406976744186046,
"activationCount": 186,
"sampleConfidence": 0.9996415770609319,
"bestPortfolioSize": 3,
"shadowTotalReturn": 0.5042021076847696,
"avgForwardReturn1D": 0.005790469814899956
},
{
"comboQuality": 0.9652726810039046,
"fitnessScore": 1.0814744721363674,
"lookbackDays": 63,
"returnLift1D": -0.00013760433757236887,
"activationRate": 0.6257668711656442,
"activationCount": 204,
"sampleConfidence": 0.9973856209150327,
"bestPortfolioSize": 4,
"shadowTotalReturn": 0.8772378818131723,
"avgForwardReturn1D": 0.006373702684329608
}
],
"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": "5c61bcecb716323eb698b1e266e824544ef69f1538453c5752fb3f75296f6832",
"size": 13,
"members": [
"FLNC",
"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