Quant Model Peer Review overview

Conducts rigorous peer review of quantitative models before production deployment — performing code review for implementation correctness and computational efficiency, verifying mathematical derivations and statistical methodology (hypothesis testing, multiple comparison corrections), auditing data pipeline integrity and point-in-time correctness, reviewing parameter sensitivity analysis and stress test results, and assessing model risk including regime-dependence and tail behaviour. Produces review verdicts with required changes, conditional approvals, or rejection rationale. Excludes model ideation and research direction setting.