Share Class Evolution
Check each share class against a reference class and flag unexpected drift.
Share Class Evolution checks each share class's NAV return against a chosen reference share class of the same sub-fund, flagging share classes that drift in statistically unexpected ways. It spots the anomaly without needing to fully recalculate every impact. It answers: is this share class moving out of line with its reference class after accounting for FX, fees, and hedging?
How it works
It looks for pricing errors at the share-class level by studying how each share class's NAV return deviates from a single reference class in the same sub-fund. Rather than fully recalculating every impact, it uses regression and time-series analysis to account for the legitimate reasons two classes diverge (FX and hedging, fees, distribution and flow policy), then examines the residual deviation. It sets robust statistical bounds on that residual and raises a standard anomaly, or a major anomaly with wider bounds for extreme cases.
What you get
- The deviation over time between a share class's return and its reference class's return.
- Analysis that accounts for the usual sources of legitimate difference (FX and hedging, fees, distribution and flow policy).
- Statistical bounds for acceptable deviation.
- Two events: a Share Class Evolution Anomaly (an unexpected NAV move) and a Major Anomaly (the same check with wider bounds for extreme cases).
How to use it in Spark
The deviations and anomaly events arrive as data in your workspace. Track them in a data view or on a canvas, and let a workflow or the Agent act when an anomaly fires.