Set out where active management's fundamental law is useful in practice and where it falls short

The fundamental law is a powerful way to think about where active return comes from, to compare strategies and to quantify the cost of constraints, but it is hard to apply precisely. The information coefficient is an ex ante estimate that must be inferred from a noisy track record and may change over time. Breadth assumes independent decisions, yet forecasts for stocks exposed to the same factor, or monthly bets on a slow-moving signal, are correlated, so counting each as a separate bet overstates breadth. The law also ignores transaction costs and treats the transfer coefficient as fixed. The trap is treating an IR computed from the law as a precise forecast rather than a guide.