Return Attribution: Decomposing the Sources of Portfolio Return

Return attribution explains which investment decisions contributed to a portfolio's realized return or to its return relative to a benchmark.

It is a branch of Performance Attribution. It should not be confused with return measurement, which calculates the portfolio's return, or performance appraisal, which attempts to judge the quality of the investment process.

Active-return attribution

For an active portfolio, the starting identity is often:

Active Return = Portfolio Return - Benchmark Return

If a portfolio returns 9% and its benchmark returns 7%, active return is 2 percentage points.

Attribution asks how the portfolio's active decisions produced that 2-point difference.

Common decomposition

In an equity portfolio grouped by sectors or other categories, Brinson Attribution commonly separates active return into:

• Allocation Effect: the impact of overweighting or underweighting categories;
• Selection Effect: the impact of portfolio securities performing differently from their category benchmark; and
• Interaction Effect: the joint effect of active category weight and within-category relative performance.

Other portfolios require different decompositions. Fixed-income attribution may emphasize duration, yield-curve, spread, credit, and currency decisions. Factor attribution may explain returns through systematic exposures.

Return contribution is not the same thing

Return contribution generally asks how much a holding, segment, or asset class contributed to the portfolio's total return.

Return attribution asks how investment decisions explain relative or decision-based performance, usually against a benchmark.

A large return contribution does not necessarily represent positive active value added. A large benchmark weight can create a large contribution even when the position merely matches the benchmark.

Results depend on the model

Attribution output changes with:

• the chosen benchmark;
• category definitions and hierarchy;
• beginning versus average weights;
• holdings versus transaction data;
• arithmetic versus geometric frameworks;
• treatment of cash, fees, currency, and derivatives; and
• multi-period linking conventions.

Two valid attribution systems can therefore report different component effects while still reconciling to the same total performance under their respective conventions.

Attribution is descriptive, not proof of skill

A positive selection effect in one period means the portfolio's holdings outperformed the corresponding benchmark segment under the selected attribution method. It does not prove persistent security-selection skill.

Likewise, positive allocation effects do not establish that a manager can repeatedly time sectors or asset classes.

Attribution explains how realized performance was generated. Skill assessment requires broader evidence across time, benchmarks, risk, costs, and the investment process.

Sources

• CFA Institute, Portfolio Performance Evaluation, 2026
• CFA Institute, 2026 CIPM Level I Topic Outline: Return Attribution and Benchmark Analysis
• CFA Institute Research Foundation, Performance Attribution

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