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Arithmetic Mean Return

Simple average of periodic returns. Sum of returns divided by the number of periods.

When to use: Use as the unbiased estimator of expected return for a single future period — the right input to risk models like CAPM and to volatility/Sharpe calculations. Do NOT use to describe realized cumulative growth (use Geometric Mean Return for that).

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Formula

AMR=1nt=1nrtAMR = \frac{1}{n} \sum_{t=1}^{n} r_t

Variables

SymbolNameDescriptionUnit
AMRArithmetic Mean ReturnSimple average periodic return as a decimal%
ReturnsPeriodic ReturnsSequence of periodic returns as decimals (e.g. 0.05 for 5%)%

Real-Life Examples

Example 1: Three-Year Returns

Annual returns: 50%, −30%, 20%.

Given

Returns =

Step-by-Step

1.Sum = 0.50 + (−0.30) + 0.20 = 0.40
2.AMR = 0.40 / 3 ≈ 0.1333 = 13.33%
Result:0.13

Arithmetic mean of 13.33%. This is the right input to forward-looking models (CAPM expected return, Sharpe denominator inputs) but overstates realized growth — geometric mean is 8.01%.

Frequently Asked Questions

Because arithmetic mean is the unbiased estimator of next-period's expected return — the right number for forward-looking risk models. Geometric mean is the biased downward estimator that captures realized compounding, but underestimates expected future returns.

Approximately: AMR − GMR ≈ σ²/2 (Jensen's inequality). At 20% volatility, expect about a 2pp gap; at 40% volatility, about 8pp. This is sometimes called "variance drag" or "volatility tax."

Forward-looking risk and expected-return models (CAPM, MPT optimization, Sharpe ratios) use arithmetic mean. Backward-looking realized performance disclosures use geometric mean. Confusing the two is one of the most common errors in performance reporting.