ACG for Quants

Quantitative-finance systems do more than compute. They admit data, bind time-varying identities, transform evidence, test hypotheses, migrate research into production, construct constrained portfolios, authorize market effects, and explain outcomes. Each transition carries an implicit constitution: source and licensing rules, point-in-time requirements, leakage controls, risk and mandate limits, model approvals, execution authority, and retirement conditions. This paper applies Ableman Constitutional Governance (ACG) to that lifecycle. ACG is the corpus-level architectural family in which authority, jurisdiction, identity, admissibility, evidence, refusal, effects, standing, and revision remain explicit. It does not replace econometrics, optimization, market microstructure, model-risk management, security controls, regulation, or professional judgment. It makes their authority and dependency relations inspectable. The governing principle is admissibility before consequential reliance. A file, mapping, factor, backtest, forecast, portfolio, or order proposal does not gain standing merely by existing. It is evaluated for a declared purpose, time, jurisdiction, authority, evidence state, and effect class. Valid outcomes include admission, bounded admission, hold, and refusal. Refusal is not automatically an outage; in high-stakes systems, it can be the correct continuation. The paper develops point-in-time identity governance, bitemporal data admission, a Factor Semantic Specification, cross-substrate equivalence claims, constitutional portfolio construction, pre-admitted execution envelopes, factor-authority retirement, and bounded attribution. It distinguishes decision receipts from proof of data truth, causal explanation, legal compliance, optimality, or market effect. It also maps the proposal through Possibility, Specification, CM1, CM2, Instance Configuration, Implementation Realization, Evidence, and Revision. This is a conceptual architecture and research agenda, not investment advice, a trading strategy, a compliance determination, or evidence that an implementation improves returns or reduces risk. External financial, legal, technical, and empirical review remains required before publication or use in a consequential trading system.