Volatility Impact Calculator

Two portfolios with the same average return can end at very different places. A portfolio averaging 10% with 5% volatility lands differently than one averaging 10% with 20% volatility. The geometric return — what actually compounds — drops as volatility rises. 100,000 at 10% average return over 30 years: arithmetic FV is 1,745,000; with 20% volatility, realistic geometric FV is 1,006,000 — a 739,000 difference despite the same headline average. Volatility is a real cost.

Quick example

With principal of 100,000 and average annual return of 10% (plus volatility of 20% and years of 30), the result is 738,674.54.

Which inputs matter most

You enter Principal, Average Annual Return, Volatility (std dev), and Years.

What's happening under the hood

Geometric return approximation: arithmetic mean minus half the variance. Valid for small-to-moderate volatility; actual geometric return simulated from return distributions can differ slightly.

Where this fits in planning

This is a "what-if" tool, not a forecast. It helps to test ideas: what happens to the result as the Principal or the Average Annual Return changes. The value is in the scenarios you run, not the single answer you get from the defaults.

What this doesn't capture

This is a simplified model that holds its assumptions constant. Real outcomes vary with market conditions, costs, taxes, and timing, so the figure is best read as one scenario rather than a forecast.

Average return against realised return

Average return and realised return are not the same number, and volatility is the reason. A portfolio that falls 50% then rises 50% averages zero and is down 25%. The calculator applies the standard variance drag approximation, subtracting half the variance from the arithmetic mean to estimate the compound rate, so at the defaults a 10% average with 20% volatility behaves closer to 8% over thirty years.

Where the approximation holds

The approximation holds well for moderate volatility and drifts at the extremes, where the true geometric return falls further below the estimate than the formula suggests. It also treats volatility as constant, whereas in practice it clusters. The output is useful for showing that two portfolios quoting the same average return can finish far apart, rather than for predicting where either one lands.