Sector Data

Sector
Port Wt %
Bench Wt %
Port Ret %
Bench Ret %
Portfolio: 100.0% Benchmark: 100.0%
Brinson-Fachler Attribution
Active Return = Allocation + Selection + Interaction
Allocation = (wp - wb) × (Rb,i - Rb) | Selection = wb × (Rp,i - Rb,i) | Interaction = (wp - wb) × (Rp,i - Rb,i)
Ryan O'Connell, CFA
Calculator by Ryan O'Connell, CFA

Attribution Results

Total Active Return --
Portfolio Return --
Benchmark Return --
Allocation Effect --
Selection Effect --
Interaction Effect --
Residual --

All returns and effects are for the analysis period. Effects shown as percentages.

Per-Sector Breakdown

Sector Active Wt (%) Active Spread (%) Allocation (%) Selection (%) Interaction (%) Total (%)

Formula Breakdown

Brinson-Fachler: Active Return = Σ Allocation + Σ Selection + Σ Interaction

Active Return Interpretation

Active Return Rating Interpretation
≥ 2% Strong Outperformance Significant positive active return
0.5 to 2% Moderate Outperformance Meaningful positive active return
-0.5 to 0.5% Neutral Returns roughly match benchmark
-2 to -0.5% Moderate Underperformance Meaningful negative active return
< -2% Strong Underperformance Significant negative active return

Thresholds are educational heuristics. Interpretation depends on the analysis period and investment strategy.

Model Assumptions
  • Uses the Brinson-Fachler three-effect decomposition (allocation, selection, interaction)
  • Single-period attribution (no compounding effects across periods)
  • Returns are arithmetic (not geometric/linked)
  • Sector definitions are mutually exclusive and collectively exhaustive
  • Benchmark is fully replicated (all sector weights known)
  • No currency effects (domestic attribution only)

For educational purposes. Not financial advice. Market conventions simplified.

Understanding Performance Attribution

What is Performance Attribution?

Performance attribution decomposes the difference between a managed portfolio's return and its benchmark return into components that explain the sources of active performance. It answers the fundamental question: why did the portfolio outperform or underperform?

The Brinson-Fachler model (the most widely used attribution framework in institutional portfolio management) breaks active return into three effects:

Allocation Effect

Measures the impact of overweighting or underweighting sectors relative to the benchmark. Rewards overweighting sectors with above-average benchmark returns.

Selection Effect

Measures the impact of picking securities that outperform the sector benchmark. Uses benchmark weights to isolate pure stock-picking skill.

The Interaction Effect

The interaction effect captures the joint impact of both overweighting a sector and selecting better securities within it. It is positive when a manager overweights sectors where they also have superior selection skill.

Brinson-Fachler Decomposition
Allocation: (wp,i - wb,i) × (Rb,i - Rb)
Selection: wb,i × (Rp,i - Rb,i)
Interaction: (wp,i - wb,i) × (Rp,i - Rb,i)
Active Return = Σ Allocation + Σ Selection + Σ Interaction
BF vs. BHB: The Brinson-Fachler model subtracts the total benchmark return (Rb) in the allocation formula, while the Brinson-Hood-Beebower (BHB) model uses raw benchmark sector returns directly. Both models produce three effects (allocation, selection, interaction); the difference is the allocation baseline, not the number of components.

Practical Applications

  • Manager evaluation: Determine whether active returns come from allocation skill, selection skill, or both
  • Process assessment: Verify that the investment process generates returns from intended sources
  • Client reporting: Communicate performance drivers transparently to stakeholders
  • Portfolio construction: Learn from past attribution to refine future decisions

Related Topics

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Frequently Asked Questions

Performance attribution analysis decomposes the difference between a managed portfolio's return and its benchmark return into components that explain the sources of excess performance. It answers why a portfolio outperformed or underperformed by isolating the impact of asset allocation decisions, security selection skill, and their interaction. This is a core tool in institutional portfolio management for evaluating investment managers.

The Brinson-Fachler model (also called the three-effect decomposition) is the most widely used performance attribution framework. It breaks active return into three effects: allocation (over/underweighting sectors that outperform), selection (picking better securities within sectors), and interaction (the cross-effect of both). This differs from the Brinson-Hood-Beebower (BHB) model, which also shows three effects but uses raw sector benchmark returns (rather than excess returns) in the allocation formula. The BF model is preferred because its allocation effect is more intuitive — it is positive when the manager overweights outperformers or underweights underperformers relative to the total benchmark.

The allocation effect measures the impact of overweighting or underweighting sectors relative to the benchmark. It rewards overweighting sectors with above-average benchmark returns: Allocationi = (wp,i - wb,i) × (Rb,i - Rb). The selection effect measures the impact of picking securities that outperform the sector benchmark. It uses benchmark weights to isolate pure stock-picking skill: Selectioni = wb,i × (Rp,i - Rb,i). In short, allocation is about where you invest, and selection is about what you pick within each sector.

The interaction effect captures the joint impact of both overweighting a sector and selecting better securities within it: Interactioni = (wp,i - wb,i) × (Rp,i - Rb,i). It is positive when a manager overweights sectors where they also have superior security selection, and negative when overweighting sectors with poor selection. In practice, interaction effects are often small and may be combined with either the allocation or selection effect, depending on firm conventions.

Portfolio managers and their clients use attribution analysis to: (1) evaluate whether active returns come from skill or luck, (2) identify which allocation or selection decisions added or destroyed value, (3) assess consistency of the investment process over time, (4) communicate performance drivers to stakeholders and investment committees, and (5) refine future portfolio construction by learning from past attribution patterns. It is standard practice in institutional investment management and a required topic for CFA and FRM certification exams.

Single-period attribution has several limitations: (1) results are benchmark-dependent and change with different benchmark choices, (2) sector classification can significantly affect attribution results (classification sensitivity), (3) arithmetic single-period returns do not compound correctly over multiple periods — geometric linking methods like Carino or GRAP are needed for multi-period attribution, (4) it assumes sectors are mutually exclusive and collectively exhaustive, and (5) it does not capture timing effects within the period.
Disclaimer

This calculator is for educational purposes only and uses the Brinson-Fachler single-period attribution model. Actual attribution analysis may require geometric linking for multi-period analysis, currency adjustments, and benchmark-specific methodology. Results depend on sector classification and benchmark choice. This tool should not be used as the sole basis for investment decisions.

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