Equity-sleeve coverage100.0%99.7% covered of 99.7% retained equity weight.
Total-fund coverage99.7%Company fundamentals as a share of 100.0% reported fund weight; no reallocation.
Non-company exposure0.3%Cash, derivatives, and other non-equity rows are excluded · tradingview_etf_holdings · Jul 20, 2026 · current.
Complete mapped company sleeve31/31 mapped companies have stored fundamentals, covering 100.0% of the retained company sleeve and 99.7% of fund weight. The remaining 0.3% is non-company exposure, not missing companies.
XLU — State Street Utilities Select Sector SPDR ETF factor map
Return factors and risk factors built from stored company fundamentals, price tape, themes, event evidence, liquidity, and flow datasets.
Companies31Ranked inside this universe
Factors5034 ready · 16 partial
Coverage100%Average ready-factor coverage
As ofJul 21, 9:30 PM GMT+8Latest stored factor input
Full factor lab detail queuedThe initial factor map is loaded from the compact snapshot; full histories, heatmaps, validation matrices, and lenses hydrate on demand.
Factor workflow
Navigate the factor engine without scrolling the whole report
Start with attribution quality, move into the action book, then inspect individual factor evidence only when needed.
Factor exposure engine
Explain XLU — State Street Utilities Select Sector SPDR ETF through true factor returns
Daily stock-level cross-sectional regressions estimate factor returns from company returns and reusable economic factor exposures. Sector, industry, theme, and country are reporting lenses, not dummy factors used to force-fit the universe return.
For each stored trading day, company returns are regressed against reusable company-level factor exposures. The common market column captures the broad universe tape; style factors explain tilts around that tape.
Lens policyNo fake fit from buckets
Sector, industry, country, and theme are reporting lenses only; they are not dummy variables used to force-fit returns.
Attribution splitWhat is investable versus only explanatory
6 usable factors · 42 diagnostic factors
Common tape+1.15%Broad universe move before active factor interpretation.Rewarded / usable factors+0.04%3 rewarded · 3 risk-controlDiagnostic factors+0.96%42 diagnostic · 0 blockedResidual-0.04%Idiosyncratic return that should flow into company-level research.
Attribution policy. Separate common tape, investable rewarded factors, diagnostic factors, and residual. Diagnostic factors explain movement but are not portfolio-sizing inputs.
Factor action bookWhat to overweight, hedge, block, or research next
Underweight · -0.06% actionable return
Active tilts3Risk controls3Blocked0Research-only42Regime-adjusted3
Hedge / cap exposureConviction 62 · risk budget 5%
Contribution
-0.39%
Factor return
+0.67%
Exposure
-0.57
Short squeeze pressure should cap, hedge, or screen fragile exposures rather than drive return chasing.
Regime-aware sizingSmall / validation pending
No stored regime evidence · best n/a · worst n/a · n/a% survival
No stored regime validation yet; keep sizing small until regime behavior is refreshed.
Coverage passValidation watchPayoff failCrowding failRisk budget passRegime fit watch
Risk controlLiquidityRisk-control factor
Hedge / cap exposureConviction 59 · risk budget n/a%
Contribution
+0.03%
Factor return
-0.26%
Exposure
-0.11
Liquidity should cap, hedge, or screen fragile exposures rather than drive return chasing.
Regime-aware sizingSmall / validation pending
No stored regime evidence · best n/a · worst n/a · n/a% survival
No stored regime validation yet; keep sizing small until regime behavior is refreshed.
Coverage passValidation watchPayoff failCrowding watchRisk budget watchRegime fit watch
Use the action book as a review order. Active tilts require validation, breadth, uniqueness, controlled crowding, and regime survival; diagnostic rows remain research-only.
Model fit disciplineWhen factor attribution is reliable enough to use
Usable factor fit
Current stock-level fit65%Weighted R-squared across latest company returns.Average daily fit63%How often the model explains day-to-day cross-sectional moves.Fit stability67%Share of stored sessions with usable stock-level factor fit.Residual cost+1.62%Average stock-level error; gross residual +1.33%.
Not an accounting identity. R-squared is a stock-level fit diagnostic, not a promise that factors explain every portfolio return dollar. The residual board remains the source of company-specific work.
Use factors as the first pass, then verify residual groups and company-specific outliers before sizing.
Factor trust dashboardCan this attribution guide positioning?
Usable with checks
Trust score61
Use smaller factor tilts; validate residual clusters and crowded factors before sizing.
Positioning guidanceUsable with checks
Use smaller factor tilts; validate residual clusters and crowded factors before sizing.
Weakest fit dayMay 29, 2026
21% fit · RMSE +0.56%
Residual-dominated days7
Latest fit 80% · average 63%
Required checks before sizing2 passed
Stock-level fitpass63 · Latest and average stock-level fit are strong enough to start with factor attribution.
Residual loadpass20 · Residual sleeve is controlled enough for a factor-first review.
Validation depthwatchn/a · Run forward validation before treating factor payoffs as durable.
Crowding controlfail100 · Top factors or redundant factors dominate; cap position size and avoid double counting.
Diagnostic factor loadfail50 · Diagnostic-only factors explain too much movement; do not size them directly.
Failure modes5 checks
Weakest fit dayhigh2026-05-29 had only 21.0% stock-level explanatory fit.
Validation depthmediumForward validation is not strong enough to treat every factor payoff as durable.
Crowding controlhighA small number of sleeves or overlapping factors can dominate the attribution.
Diagnostic factor loadhighToo much movement is explained by diagnostic-only factors that should not be direct sizing inputs.
Residual-dominated daysmedium7 stored sessions had more residual than modeled factor fit.
Factor reliability boardWhich factors are investable, confirming, or noisy
49 average reliability · 0 decision-grade factors
Decision-grade tilts0Validated enough for active factor interpretation
No factor clears all reliability gates yet.
Usable confirmation1Useful when independent evidence agrees
Earnings revision pressureUse as a confirming factor alongside other independent evidence.
Reliability
61
Validation
n/a
Crowding
66
Noisy or incomplete4Needs better validation, coverage, or stability
LiquidityUse as a descriptive exposure until forward tests are populated.
Reliability
52
Validation
n/a
Crowding
58
BetaUse as a descriptive exposure until forward tests are populated.
Reliability
49
Validation
n/a
Crowding
74
SizeUse as a descriptive exposure until forward tests are populated.
Reliability
49
Validation
n/a
Crowding
58
Insider alignmentUse as a descriptive exposure until forward tests are populated.
Theme alignmentUse only as a warning or confirmation; avoid double-counting this factor.
Reliability
45
Validation
n/a
Crowding
100
Macro / theme tailwindUse only as a warning or confirmation; avoid double-counting this factor.
Reliability
45
Validation
n/a
Crowding
100
Institutional flowUse only as a warning or confirmation; avoid double-counting this factor.
Reliability
45
Validation
n/a
Crowding
100
Revenue acceleration leadershipUse only as a warning or confirmation; avoid double-counting this factor.
Reliability
41
Validation
n/a
Crowding
100
No factor currently clears the decision-grade validation, stability, and uniqueness gates.Some factors are highly correlated with peers, so do not add their attributions together mechanically.Some factors are descriptive only until forward validation or coverage improves.
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