BalanceCheat
ENDE

INTERPRET RESULTS

P10, P50 and P90: read the percentile, unit and direction together

In BalanceCheat, P10, P50 and P90 are cumulative sample percentiles: low to high in the output distribution. P50 is the median. Whether the low or high tail is unfavorable depends on the metric. Always confirm the convention before comparing these labels with another report.

Cumulative percentiles in an illustrative ordered sample
LabelNative interpolated valueReading
P109 EURkLow cumulative percentile; not automatically the worst case
P5045 EURkMedian; not automatically Base or mean
P9081 EURkHigh cumulative percentile; not automatically favorable
On this page
  1. Why a percentile need not be an observed value
  2. A P90 exceedance value reverses the direction
  3. Which tail is adverse depends on the financial output
  4. A percentile band is not a confidence interval for the mean
  5. Read the output in its original context

Why a percentile need not be an observed value

Use ten synthetic observations, in EURk: 0 → 10 → 20 → 30 → 40 → 50 → 60 → 70 → 80 → 90. These are an illustration for reading statistics, not a financial forecast or a Monte Carlo run. Here 1 EURk means EUR 1,000.

The native statistics routine uses linear interpolation at zero-based position (n − 1) × p. P10 lies at position 0.9, between 0 and 10, and equals 9 EURk. P50 lies at 4.5 and equals 45 EURk; P90 lies at 8.1 and equals 81 EURk.

A small empirical sample and an interpolated quantile need not place exactly the named percentage of observations below the printed value. The empirical CDF is a different calculation: at 20 EURk, three of ten observations are at or below the threshold, so the CDF is 30%.

A P90 exceedance value reverses the direction

Some energy-project reports use P90 to mean an amount expected to be met or exceeded with 90% probability. NREL documents this exceedance convention. For a continuous distribution, that corresponds to the low cumulative P10, not the cumulative P90 used in BalanceCheat.

Ask whether the label means “at or below” or “met or exceeded.” With discrete outcomes or ties, also check the inequality and quantile method. Do not compare two P90 figures solely because their labels match.

Two conventions that must not be mixed
ConventionMeaning of 90Position
Cumulative P90About 90% of the distribution is at or below the valueHigh tail
P90 exceedanceThe value is met or exceeded with 90% probabilityLow tail for a continuous distribution

Which tail is adverse depends on the financial output

The unit tells you what is being measured; the metric tells you how to interpret direction. The same percentile position can indicate a shortfall in one output and resilience in another.

Direction under the cumulative convention
OutputGenerally adverse directionWhat to compare
Cash / Liquidity HeadroomLowerThe low tail against minimum cash or zero headroom
EBITDA / Equity ValueLower, other assumptions equalThe low tail against the decision threshold
Required FundingHigherThe high tail against available financing
A cost or cash outflowHigherThe high tail against budget or liquidity capacity

A percentile band is not a confidence interval for the mean

P10–P90 describes spread in modeled outcomes. It does not measure uncertainty in the estimated mean and does not guarantee that 80% of real future outcomes will fall inside the interval. A confidence interval for a mean is a different statistical object requiring its own method and assumptions.

Check the valid denominator. If 100 runs were completed, 90 were valid and 18 valid outcomes crossed a threshold, the reported conditional frequency would be 18 / 90 = 20%, not 18%. Investigate the ten invalid results before using that percentage. This arithmetic example is illustrative and separate from the ten-value percentile sample.

Read the output in its original context

Record the output name, currency and scale, period, scenario, input distributions, valid-run count and percentile convention. Base, median and mean answer different questions and can differ.

Use the Monte Carlo workflow to generate native results. The results reference explains available statistics and stochastic constraints explains conditional denominators. For the method itself, read Monte Carlo in finance.

Sources and conventions

Synthetic examples. Model-based results were reconciled with the current BalanceCheat calculations; assumptions, units and boundaries are specified in each example.