Execution Certificates for Open Finance: Auditable Data Availability, Latency, and Cost in Learned Lead–Lag Trading

Open-finance interfaces make market data and trading services programmable, but an API response is not an executable signal. Economic information depends on data receipt, inference completion, and feasible order arrival. We propose an execution certificate: a machine-readable contract that binds a learned lead–lag edge to data-availability timestamps, a lower bound on residual alpha, a size-matched upper bound on cost, and simultaneous uncertainty. We prove that coarse bars need not identify subbar delay ordering, derive a finite-response latency budget, and show that the optimal position is zero unless residual alpha clears cost. A frozen prequential diagnostic on 11 exchange-traded funds and 761 weekly test observations provides a deliberately negative result. The lag graph’s Sharpe ratio falls from 0.727 before cost to 0.152 at 10 basis points per traded dollar, and its annualized mean difference from momentum has a paired 95% interval of [−9.49, 1.68] percentage points. Weekly bars identify cost fragility, not millisecond decay. We therefore specify a prospective two-venue WebSocket protocol in receipt time. The framework turns model output into an auditable capital-markets decision while preserving abstention as a valid FinTech outcome.