Portfolio data quality guide
Portfolio data quality
Portfolio data quality is part of the result, not a footnote. Source, coverage, freshness, price basis, missing observations, and assumptions shape what a calculation can support.
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Start with source and coverage
Identify the provider, observation dates, common history, and any instruments with shorter or interrupted records. A portfolio calculation can be internally consistent while answering a narrower question than its label suggests if one sleeve lacks comparable history.
Check freshness and price basis
Price observations can arrive at different times and may use different adjustment conventions. Note whether values are current enough for the question, whether distributions or splits are handled consistently, and whether currency or settlement assumptions are being mixed into the comparison.
Treat caveats as decision inputs
Quality metadata does not make incomplete history complete. It tells you where interpretation should be narrower, which comparison should be rerun, and which assumptions deserve attention. SumWorth surfaces trust notes next to the research so a precise-looking number does not outrun its evidence.
Evidence boundary
Data-quality notes help explain the limits of a historical or modeled result. They do not turn incomplete observations into complete evidence or remove market uncertainty.