AI & Model Risk
AI Signals in Equity Markets: Validation Is the Edge
The durable advantage is not a louder model. It is evidence that the model still works under stress, drift, and changing market structure.
Move past the black-box signal
NIST’s AI Risk Management Framework remains a practical reference for governing AI risk, and NIST is revising AI RMF 1.0. The August TEVV-Athlon draft goes further into testing, evaluation, verification, and validation of AI systems.
ATLAS4 distinction: a model output is an observation candidate, not a trade instruction. Provenance, drift, missingness, latency, and counter-evidence travel with the signal.
What institutional users should demand
- Time-aligned inputs with reproducible lineage.
- Out-of-sample and stress testing appropriate to the decision.
- Clear separation between predictive performance and causal explanation.
- Documented invalidation conditions and human review paths.
No model can make a market call 100% correct. The objective is calibrated confidence and bounded risk authority.
Primary sources
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