Equity-sleeve coverage43.7%43.7% covered of 99.8% retained equity weight.
Total-fund coverage43.7%Company fundamentals as a share of 100.0% reported fund weight; no reallocation.
Non-company exposure0.2%Cash, derivatives, and other non-equity rows are excluded · tradingview_etf_holdings · Jul 17, 2026 · current.
Partial mapped company sleeve16/16 mapped companies have stored fundamentals, covering 43.7% of the retained company sleeve and 43.7% of fund weight. The remaining 0.2% is non-company exposure, not missing companies. Separately, 14 equity holdings (56.2% of fund weight) remain unmapped.
Return factors and risk factors built from stored company fundamentals, price tape, themes, event evidence, liquidity, and flow datasets.
Companies16Ranked inside this universe
Factors5034 ready · 16 partial
Coverage98%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 BUG — Global X Cybersecurity 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
17 usable factors · 30 diagnostic factors
Common tape-17.61%Broad universe move before active factor interpretation.Rewarded / usable factors-16.49%8 rewarded · 9 risk-controlDiagnostic factors+0.99%28 diagnostic · 2 blockedResidual+0.02%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
Overweight · -7.54% actionable return
Active tilts8Risk controls9Blocked2Research-only28Regime-adjusted8
Small / validation pendingConviction 64 · risk budget n/a%
Contribution
-1.16%
Factor return
+4.67%
Exposure
-0.25
Cash-conversion compounder is a rewarded factor with negative contribution; reduce high exposure until payoff repairs.
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 passCrowding failRisk 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 fit99%Weighted R-squared across latest company returns.Average daily fit67%How often the model explains day-to-day cross-sectional moves.Fit stability75%Share of stored sessions with usable stock-level factor fit.Residual cost+2.64%Average stock-level error; gross residual +1.07%.
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 for the common tape and major style tilts; send weak-fit pockets into residual research.
Factor trust dashboardCan this attribution guide positioning?
Usable with checks
Trust score69
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 dayJul 17, 2026
6% fit · RMSE +0.28%
Residual-dominated days9
Latest fit 96% · average 67%
Required checks before sizing2 passed
Stock-level fitpass67 · Latest and average stock-level fit are strong enough to start with factor attribution.
Residual loadpass4 · 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 loadwatch31 · Diagnostic-only factors are meaningful; use them for triage rather than direct sizing.
Failure modes5 checks
Weakest fit dayhigh2026-07-17 had only 6.0% 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 loadmediumToo much movement is explained by diagnostic-only factors that should not be direct sizing inputs.
Residual-dominated daysmedium9 stored sessions had more residual than modeled factor fit.
Factor reliability boardWhich factors are investable, confirming, or noisy
55 average reliability · 0 decision-grade factors
Decision-grade tilts0Validated enough for active factor interpretation
No factor clears all reliability gates yet.
Usable confirmation0Useful when independent evidence agrees
No confirmation factors are available.
Noisy or incomplete8Needs better validation, coverage, or stability
SizeUse as a descriptive exposure until forward tests are populated.
Reliability
57
Validation
n/a
Crowding
76
LiquidityUse as a descriptive exposure until forward tests are populated.
Reliability
53
Validation
n/a
Crowding
55
Macro / theme tailwindUse as a descriptive exposure until forward tests are populated.
Reliability
52
Validation
n/a
Crowding
65
Margin recoveryUse as a descriptive exposure until forward tests are populated.
Price momentumUse only as a warning or confirmation; avoid double-counting this factor.
Reliability
59
Validation
n/a
Crowding
100
Relative leadershipUse only as a warning or confirmation; avoid double-counting this factor.
Reliability
64
Validation
n/a
Crowding
100
Institutional flowUse only as a warning or confirmation; avoid double-counting this factor.
Reliability
60
Validation
n/a
Crowding
100
Volatility regime betaUse only as a warning or confirmation; avoid double-counting this factor.
Reliability
52
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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