Search the docs⌘K
Glossario
Advanced
ENIT

Return-to-drawdown ratio

UPDATED 2026-07-25

The return-to-drawdown ratio is a strategy's return over a period divided by the size of its max drawdown in that same period — the return earned per unit of worst peak-to-trough loss. It answers "how much return did this strategy produce for the deepest fall it put up with?", which a return figure on its own cannot say. It is a standard, publicly known ratio, not a proprietary Fincanva measure.

Also seen as: NP/DD, NPDD, NP max DD, net profit ÷ maximum drawdown

How is the return-to-drawdown ratio calculated?

The ratio divides the period's return by the absolute size of the max drawdown, so the drawdown's minus sign does not flip the result.

return-to-drawdown ratio=returnmax drawdown\text{return-to-drawdown ratio} = \frac{\text{return}}{\lvert\text{max drawdown}\rvert}

where: return is the period's return (the whole-period return for the headline figure, that year's return for a per-year figure), max drawdown is the largest peak-to-trough fall in the same period, and the vertical bars mean its absolute value — the drawdown's size without its minus sign.

Why is it a ratio and not a percentage?

The return-to-drawdown ratio is a plain number, not a percentage, because it divides one percentage by another and the units cancel out. A value of 4.0 means the return was four times the size of the worst drawdown; it does not mean 4%, and it does not mean 400%.

Since a percentage divided by a percentage has no unit, the figure is shown as a bare number everywhere it appears in Fincanva — the metrics table, the by-year table, the Strategy analytics table, and the heatmap's NP/DD column. Reading it as a percentage is the most common mistake made with this metric, and it is why the canonical name carries the word ratio.

Defaults in Fincanva

  • The metrics table shows it in the Drawdown group as the row Return-to-drawdown ratio, as a plain number.
  • The by-year table gives a Return-to-drawdown ratio column per calendar year, and the Strategy analytics table gives one per strategy inside a Combined.
  • The monthly returns heatmap carries the same per-year figure in its compact NP/DD column — net profit divided by maximum drawdown, the same quantity under an abbreviated label.
  • It turns negative when the period's return is negative, because the denominator is always a positive size: a negative ratio means the strategy lost money over that period.
  • Where the figure is not available for a period, Fincanva shows "—" rather than a number.

Worked example

A strategy returns +80% over its backtest and its max drawdown in the same period is −20%. The ratio is 80 ÷ 20 = 4.0: four units of return for every unit of the worst fall.

Compare a second strategy that also returns +80% but whose max drawdown was −40%. Its ratio is 80 ÷ 40 = 2.0. On return alone the two look identical; the ratio separates them by what each went through to get there.

What counts as a good value?

A higher ratio means more return per unit of the worst fall. A ratio above 1.0 means the period's return was larger than its deepest drawdown; below 1.0, the deepest fall was larger than the return earned; a negative value means the period's return was itself negative.

The ratio uses only the single deepest fall, so it says nothing about how often drawdowns happened or how long they lasted — read it next to longest drawdown for duration, and the Sharpe ratio for return measured against overall variability instead of one worst-case event. It is also period-bound: a short window containing one mild dip can produce a very high ratio.

These figures describe what a strategy would have done on historical data, not what it will do. Fincanva provides no financial advice — see Is this financial advice?.

Where this term is used

Generated · 2 pages

The pages that reference this term — so a term page is somewhere you pass through, not somewhere you land and stop.

Fincanva provides no financial advice. Backtests show what would have happened — not what will.

GLOSSARY · 193 TERMS