Performance Attribution Report Template (Brinson)

Performance Attribution Report: [Portfolio or composite name], [period]

Periodic report that explains why a portfolio's return differed from its benchmark: returns and excess return, Brinson-Fachler and Brinson-Hood-Beebower equity attribution (allocation, selection, interaction), multi-period linking, currency and fixed income attribution, risk-adjusted measures (Sharpe ratio, information ratio, tracking error), contributors and detractors, factor exposure, commentary and methodology. Based on published academic methods (Brinson and Fachler 1985; Brinson, Hood and Beebower 1986; Carino linking), which are cited by name and expressed in original formulas. The worked example is a fictional strategy of the fictional adviser Kestrel Bay Capital. Replace every [bracketed] value and every row marked Example. This is a document format, not investment, legal or accounting advice.

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Contents

1. Summary
2. Returns versus benchmark
3. Equity attribution: allocation, selection and interaction
4. Currency attribution
5. Fixed income attribution
6. Risk-adjusted measures
7. Contributors and detractors
8. Factor exposure
9. Commentary and actions
10. Methodology and data
11. Glossary and references

1. Summary

Example: in the third quarter of 2026 the Global Quality Equity representative portfolio returned 3.26% gross in USD against 2.65% for the benchmark, an arithmetic excess of 60 basis points (geometric 0.59%). Stock selection added 31.5 basis points, led by industrials (22.0 basis points). Sector allocation added 15.6 basis points, mainly from the overweight in information technology and the underweight in consumer staples. Interaction added 13.3 basis points; the three effects sum to the 60.4 basis point excess (section 3.4). The only negative segment was financials (minus 6.8 basis points), where the portfolio's banks lagged. The team keeps the sector positioning and has started a review of the two weakest bank holdings (see section 9).

2. Returns versus benchmark

2.1 Period returns

Quarterly returns link the monthly returns geometrically: 1.02422 x 0.99288 x 1.01538 = 1.03257 for the portfolio and 1.01985 x 0.99226 x 1.01440 = 1.02653 for the benchmark.

Example: geometric excess = 1.03257 / 1.02653 minus 1 = 0.588%.

2.2 Reconciliation to official performance

A residual appears when a holdings-based calculation misses intraday trades, fees or cash flows. Report it rather than spreading it across the effects, and investigate when it exceeds the tolerance.

3. Equity attribution: allocation, selection and interaction

3.1 Model

For each segment $i$, with portfolio weight $w^P_i$, benchmark weight $w^B_i$, portfolio segment return $r^P_i$, benchmark segment return $r^B_i$ and total benchmark return $R_B$:

The Brinson-Fachler allocation effect ($A^{BF}$) rewards overweighting segments that beat the whole benchmark, which matches how most managers think. The Brinson-Hood-Beebower version ($A^{BHB}$) rewards overweighting any segment with a positive return. Because active weights sum to zero, both versions give the same total allocation effect; they differ by segment. This report uses Brinson-Fachler.

3.2 Single-period detail, July 2026

Weights are the average of daily weights for the month. In this Example they are held constant across the quarter to keep the arithmetic visible. Effects are in basis points (bp).

Check: 15.7 + 18.4 + 9.6 = 43.7 bp, which equals the July excess of 0.437 percentage points. Worked line for health care: allocation BF = (0.22 minus 0.15) x (1.2% minus 1.985%) = 0.07 x (-0.785%) = -5.5 bp; the segment beat zero but lagged the whole benchmark, so the overweight cost return under Brinson-Fachler while BHB shows a gain of 8.4 bp.

3.3 Monthly effects

The simple sum (59.7 bp) does not equal the quarterly arithmetic excess (60.4 bp), because returns compound across months. Section 3.4 links the effects so that they add up exactly.

3.4 Multi-period linking (Carino)

Example: $k$ for the quarter = 0.97130; monthly $k_t$ = 0.97844 (July), 1.00749 (August), 0.98533 (September); scaling factors $k_t / k$ = 1.00735, 1.03725, 1.01444.

The linked total (60.4 bp) equals the arithmetic excess for the quarter (3.257% minus 2.653%). Segment figures are rounded to 0.1 bp, so rows and columns can differ from their totals by 0.1 bp (for example, industrials shows 24.4 bp against a rounded row sum of 24.3 bp). The August and September segment detail behind the linked figures is in the appendix workbook; the linked totals reproduce from the monthly totals in section 3.3 and the scaling factors above (for allocation, 15.7 x 1.00735 minus 1.4 x 1.03725 plus 1.2 x 1.01444 = 15.6 bp). The Q3 segment returns are linked monthly returns; weighting them by the constant weights does not reproduce the quarterly totals exactly (3.24% and 2.64% against 3.257% and 2.653%), because each month compounds on a different base. Other linking methods (Menchero, GRAP, or a geometric attribution model that explains the geometric excess) give slightly different segment numbers; name the method and keep it stable.

4. Currency attribution

Use this section when currency is managed separately (for example, by an overlay). Otherwise state "Currency is not managed separately; currency returns are included in the selection and allocation effects", which is the case for the main example in section 3.

A simplified currency management effect compares portfolio and benchmark currency exposures, where $e_c$ is the return of currency $c$ against the base currency and $E_B$ is the benchmark's total currency return:

Example: $E_B$ = 0.65 x 0 + 0.20 x 1.2% + 0.15 x (-2.0%) = -0.06%; EUR effect = 0.05 x (1.2% + 0.06%) = 6.3 bp. A full currency model (for example Karnosky-Singer) also separates the forward premium, the hedging cost and the local-market return; use it when forwards are material.

5. Fixed income attribution

A duration-based decomposition for each portfolio and its benchmark:

where $y$ is the yield, $\Delta t$ the period in years, $D_{\text{mod}}$ the modified duration, $\Delta y_{\text{gov}}$ the change in government yields, $D_{\text{spread}}$ the spread duration, $\Delta s$ the change in credit spread and $\varepsilon$ the residual (convexity, roll-down, security selection and pricing).

Example (Kestrel Bay core bond sleeve, one quarter, parallel fall in government yields of 25 bp, spreads tighter by 10 bp):

The longer duration added 5 bp as yields fell and the larger credit exposure added 6 bp as spreads tightened; both are deliberate risk positions to be judged against the IPS risk budget, not as skill on their own. Where key-rate durations are available, split the curve effect into shift, twist and curvature.

6. Risk-adjusted measures

Example: trailing 36 months to 2026-09-30, annualised from monthly data, gross of fees, USD. The risk-free rate is the average 3-month government bill yield over the window.

Report the window, the frequency, the annualisation factor and whether returns are gross or net. Ratios from fewer than 36 monthly observations are unstable; label them.

7. Contributors and detractors

Absolute contribution is $w^P_j \, r_j$. Active contribution is $\left( w^P_j - w^B_j \right) \left( r_j - R_B \right)$, using the quarterly benchmark return of 2.65%. All company names are fictional.

Example: Northgate Instruments active contribution = (3.2% minus 0.8%) x (14.5% minus 2.65%) = 0.024 x 11.85% = 0.28 percentage points. Not owning Orrin Semiconductors cost 0.015 x 15.35% = 0.23 percentage points, the largest single detractor.

8. Factor exposure

Example: contribution = active exposure x factor return (for quality, 0.45 x 0.40% = 18.0 bp). The factor total is 18.0 minus 6.0 plus 5.0 plus 3.0 minus 4.2 = 15.8 bp, and the specific part is 60.4 minus 15.8 = 44.6 bp. Name the risk model, its version and its estimation universe in section 10; risk model factor definitions are usually licensed and should be described, not copied.

9. Commentary and actions

9.1 Portfolio manager commentary

[Three to six short paragraphs: market background in one paragraph, then the main intended bets and how they worked, then the surprises, then the outlook for positioning. Avoid forecasts presented as promises.]

Example: Industrials selection was the largest positive effect, driven by Northgate Instruments after it raised guidance on stronger demand for test equipment. The underweight in financials helped allocation, but the bank holdings we owned lagged their peers when net interest margin expectations fell, so selection in the sector was negative. Not owning the semiconductor name that led the benchmark was the largest single cost; the stock does not meet our return-on-capital threshold and we do not plan to buy it for benchmark reasons.

9.2 Actions and follow-up

10. Methodology and data

Present attribution numbers to clients in a way that is consistent with the official performance figures, show the period and basis, and do not imply that past attribution predicts future results. For a US registered adviser, client-facing attribution of selected holdings may be "extracted performance" under 17 CFR 275.206(4)-1; check the rule and the SEC staff Marketing Compliance FAQ before publication.

11. Glossary and references

11.1 Glossary

11.2 References

Standard and licence note

Based on published academic attribution and risk measures (Brinson and Fachler 1985; Brinson, Hood and Beebower 1986; Carino linking; Sharpe ratio), which are methods and are expressed here in original formulas, and on the SEC Marketing Rule (a US federal work) cited by section. No textbook, curriculum or vendor material is reproduced. The worked example (Kestrel Bay Capital) and all companies and figures are fictional. The text is original. Check the current official versions of the cited rules before use. This is a document format, not investment, legal or accounting advice. Template licence: MIT.