As Reuters’ opinion page argues, too many investors have “forgotten the scientific method”—forming strong views on markets without real hypothesis testing, confusing anecdotes for data, and skipping out-of-sample checks. It is timely advice after the Fed’s cut and the latest earnings season: the temptation is to narrate a straight-line rally, but robust process beats bright prediction. Start with explicit hypotheses (what would confirm vs falsify your thesis), measure the variables you can actually observe, and pre-commit to risk limits and review cadences. In practice that means: stop treating every headline as a trading signal; treat extreme conviction as a risk factor; and keep a written map from thesis → indicators → actions. That’s not anti-storytelling; it’s pro-survival.
A process-first mindset also travels well beyond equities. In AI procurement, apply the same logic: if a vendor claims productivity gains, demand controlled pilots with baseline metrics; if an infra partner promises Blackwell capacity, tie milestones to power and cooling readiness, not just PO numbers. In public policy, judge ceasefire “success” against measurable outcomes like restored banking services and school attendance, not press statements. The through-line across today’s news is that big claims need small proofs, and small proofs—accumulated—beat grand narratives that never meet the audit trail. That’s a discipline any newsroom, trading desk, or cabinet can adopt in one afternoon: write the hypothesis, define the test, and live with the results.
