Drawdown
At time t, drawdown is 1 − B_t / max(B_0…B_t), where B_t is bankroll. Maximum drawdown is the worst value over the sample. Drawdown is a path-dependent statistic — it depends on the order of returns, not just their distribution — which is why two strategies with the same Sharpe can have very different drawdown experiences.
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Definition
Drawdown
At time t, drawdown is 1 − B_t / max(B_0…B_t), where B_t is bankroll. Maximum drawdown is the worst value over the sample. Drawdown is a path-dependent statistic — it depends on the order of returns, not just their distribution — which is why two strategies with the same Sharpe can have very different drawdown experiences.
Why it matters
Drawdown is the survivability metric. A 50% drawdown requires a 100% return to recover; a 75% drawdown requires 300%. Most allocators redeem capital well before that. Risk budgets, leverage limits, and circuit breakers are usually written against drawdown, not volatility.
How it works
Compute running maximum equity, then 1 − current_equity / running_max. Track three things: max drawdown, time in drawdown, and time to recovery. Strategies that look similar on max drawdown can differ by years on time-to-recovery, which is the variable that actually fires investor redemptions.
Example
Two strategies, same max drawdown
Strategy A max drawdown
25%
Strategy A time in drawdown
8 months
Strategy B max drawdown
25%
Strategy B time in drawdown
31 months
Same headline number, very different lived experience. Strategy B is the one that triggers redemptions.
Key Takeaways
Recovery is asymmetric: a 50% drawdown needs a 100% return to break even.
Max drawdown is a single number; time-in-drawdown and time-to-recovery describe the actual investor experience.
Drawdown is path-dependent — same return distribution, different sequences, different drawdown.
Related Terms
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Returns Distribution Analyzer
Paste a returns CSV. Histogram, normal-overlay, QQ plot, skewness, excess kurtosis, Jarque-Bera test, tail-weight index. See why Sharpe alone misleads.
FAQ
Questions people ask next
The short answers readers usually want after the first pass.
Sources & References
- Calmar Ratio: A Smoother Tool — Young (1991), Futures Magazine
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Value at Risk: the loss threshold you'll exceed with probability α. Why historical VaR is brittle and what it doesn't tell you about the tail.