Maximum drawdown (MDD)
Quantitative Finance glossary · Quantitative Finance
Definition
Largest peak-to-trough decline of an equity curve: MDD = max_t ≤ Tleft[ dfracmax_s ≤ t W_s - W_tmax_s ≤ t W_s right]. Path-dependent and grows roughly with √(T) under iid Gaussian returns (Magdon-Ismail-Atiya scaling) — longer histories almost always contain deeper drawdowns. MDD drives institutional allocator decisions far more than volatility because redemption clauses and risk budgets trigger off drawdowns, not realised vol. Calmar = annual return / |MDD|.
Maximum drawdown (MDD) in plain English
Maximum drawdown answers a gut-level question: from any high point, what's the worst drop I would have suffered before recovering? It's the deepest peak-to-valley dip in your account's value over some period, usually quoted as a percentage — a portfolio that climbs to $100 then sinks to $70 has a 30 percent max drawdown. Two things make it matter more than plain volatility for big investors: it captures the real pain of watching money evaporate, and longer track records almost always contain deeper dips (roughly growing with the square root of time), so it's partly a function of how long you've been playing. Institutions care intensely because clients pull their money and risk limits get tripped by drawdowns, not by tidy volatility stats; the Calmar ratio (yearly return divided by the size of the worst drawdown) turns this into a quick reward-for-pain scorecard.
Also called: MDD
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