Independent Price Valuation
Independently check the prices used to value a fund's holdings.
Independent Price Valuation independently checks the prices used to value a fund's holdings, comparing the administrator's prices against external vendor prices and model-based expected ranges. It surfaces mispricing and stale or delayed prices that could distort the NAV. It answers: are the fund's holdings priced correctly and on time, and how much would any bad prices move the NAV?
How it works
It compares the administrator's prices against independent vendor prices and model-based estimates of where each price should fall, building an expected range for every instrument. It flags deviations and translates them into an estimated NAV impact, using each instrument's quotation date to tell a genuine mispricing from a merely delayed price, and separately detects stale prices that have not moved when they should have. Instruments without a reliable external reference, such as OTC or illiquid securities, fall out of scope, and cash and FX types are excluded entirely.
What you get
- Price deviations between the fund's prices and independent reference prices, with the resulting impact on NAV.
- Stale-price detection: which instruments have unchanged prices, for how long, and since when.
- Pricing-delay insight: how far behind the instrument quotation dates are versus the NAV date.
- Monthly price statistics (average, high, low) and how much of the portfolio could be independently checked. Cash and FX instruments are excluded, and illiquid or OTC instruments without a reference price fall out of scope.
In SPARK
The results arrive in an Independent Price Valuation Signals data object (ngt_independent_price_valuation_signals), created from the Independent Price Valuation Signal template, version 1.0.0, in the template picker's Analytics group. Each row is one portfolio position on one date, with the portfolio and reference prices, the Reference Price Deviation and its NAV impact, whether a reference valuation is missing, the stale-price date, days and NAV impact, the month's average, minimum and maximum price, and a price confidence.
The deviations and stale-price findings arrive as data in your workspace. Sort them by NAV impact in a data view, watch coverage on a canvas, and let a workflow flag material price breaks for review.