Equity-sleeve coverage100.0%98.8% covered of 98.8% retained equity weight.
Total-fund coverage98.8%Company fundamentals as a share of 100.0% reported fund weight; no reallocation.
Non-company exposure1.2%Cash, derivatives, and other non-equity rows are excluded · tradingview_etf_holdings · Jul 17, 2026 · current.
Complete mapped company sleeve19/19 mapped companies have stored fundamentals, covering 100.0% of the retained company sleeve and 98.8% of fund weight. The remaining 1.2% is non-company exposure, not missing companies.
Return factors and risk factors built from stored company fundamentals, price tape, themes, event evidence, liquidity, and flow datasets.
Companies19Ranked inside this universe
Factors5034 ready · 16 partial
Coverage100%Average ready-factor coverage
As ofJul 17, 5:00 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 CLR — Lion-Phillip S-REIT 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
14 usable factors · 32 diagnostic factors
Common tape+2.06%Broad universe move before active factor interpretation.Rewarded / usable factors-0.44%9 rewarded · 5 risk-controlDiagnostic factors+0.93%32 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
Overweight · -0.44% actionable return
Active tilts9Risk controls5Blocked0Research-only32Regime-adjusted9
OverweightPrice momentumConfirmed rewarded factor
Small / validation pendingConviction 66 · risk budget 2%
Contribution
+0.15%
Factor return
+1.57%
Exposure
+0.10
Price momentum is a rewarded factor with positive contribution and usable breadth.
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 passRegime fit watch
Small / validation pendingConviction 66 · risk budget 6%
Contribution
-0.41%
Factor return
+1.36%
Exposure
-0.30
Relative leadership 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 passRegime 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 fit79%Weighted R-squared across latest company returns.Average daily fit52%How often the model explains day-to-day cross-sectional moves.Fit stability61%Share of stored sessions with usable stock-level factor fit.Residual cost+1.52%Average stock-level error; gross residual +1.21%.
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 score60
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 dayJun 23, 2026
30% fit · RMSE +0.76%
Residual-dominated days14
Latest fit 49% · average 52%
Required checks before sizing1 passed
Stock-level fitwatch52 · Stock-level fit is usable but should be checked against residual outliers.
Residual loadpass21 · 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 loadwatch26 · Diagnostic-only factors are meaningful; use them for triage rather than direct sizing.
Failure modes6 checks
Weak stock-level fitmediumThe cross-sectional model is not consistently explaining stock returns.
Weakest fit dayhigh2026-06-23 had only 30.0% 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 daysmedium14 stored sessions had more residual than modeled factor fit.
Factor reliability boardWhich factors are investable, confirming, or noisy
53 average reliability · 0 decision-grade factors
Decision-grade tilts0Validated enough for active factor interpretation
No factor clears all reliability gates yet.
Usable confirmation3Useful when independent evidence agrees
SizeUse as a confirming factor alongside other independent evidence.
Reliability
62
Validation
n/a
Crowding
62
Earnings revision pressureUse as a confirming factor alongside other independent evidence.
Reliability
60
Validation
n/a
Crowding
60
BetaUse as a confirming factor alongside other independent evidence.
Reliability
58
Validation
n/a
Crowding
50
Noisy or incomplete8Needs better validation, coverage, or stability
LiquidityUse as a descriptive exposure until forward tests are populated.
Reliability
55
Validation
n/a
Crowding
63
Drawdown repairUse as a descriptive exposure until forward tests are populated.
Reliability
55
Validation
n/a
Crowding
64
Growth accelerationUse as a descriptive exposure until forward tests are populated.
Reliability
54
Validation
n/a
Crowding
59
LeverageUse as a descriptive exposure until forward tests are populated.
Price momentumUse only as a warning or confirmation; avoid double-counting this factor.
Reliability
67
Validation
n/a
Crowding
100
Relative leadershipUse only as a warning or confirmation; avoid double-counting this factor.
Reliability
65
Validation
n/a
Crowding
100
Catalyst evidenceUse only as a warning or confirmation; avoid double-counting this factor.
Reliability
49
Validation
n/a
Crowding
100
Institutional flowUse only as a warning or confirmation; avoid double-counting this factor.
Reliability
66
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.
Tracker