Glossary · Backtesting & Analytics
Max Drawdown
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Max drawdown (MDD) is the largest peak-to-trough decline in account equity over a period, expressed as a percentage of the peak — the single worst loss an investor would have suffered buying at the worst high and measuring to the worst subsequent low. Where a drawdown is any dip in the equity curve, max drawdown is a metric: one number summarizing the deepest of them.
Formula
Max drawdown = (Peak equity − Trough equity) ÷ Peak equity × 100
Computed over an equity curve, it means: track the running peak; at each point compute the fall from that peak; report the largest fall. Suppose a five-year NIFTY strategy backtest shows equity peaks and troughs including ₹10,00,000 → ₹8,40,000 and later ₹14,00,000 → ₹11,10,000. The falls are 16.0% and 20.7%; max drawdown = 20.7%, the deeper of the two — even though the second dip started from a much higher base. Hypothetical figures.
Why it matters
Max drawdown is the risk number most decisions hang on. It sets position size (could you fund and stomach a repeat?), feeds ratios like return-to-max-drawdown, and defines the tripwire for switching a live strategy off. Two cautions for algo traders: a backtest’s MDD is one historical sequence — the future’s worst dip is routinely deeper, which is why Monte Carlo simulation reports a distribution of drawdowns rather than one value — and comparing strategies on returns without comparing MDD is comparing engines without brakes.
In INDfolio AI, max drawdown appears in every backtest report and its plausible range in the Monte Carlo analysis.