Allocation added 0.39, selection took 0.91 and interaction 0.02, netting to a 0.53 shortfall; the GF570 Unit 8 attribution analysis traces each piece to a segment and a decision. Searches like "gf 570 unit 8 assignment example", "gf570 unit 8 sample" and "gf570 unit 8 example" land here.
What a finished GF570 Unit 8 attribution analysis looks like
An analysis of about five pages built on one attribution table. Five segments carry average portfolio and benchmark weights and returns for the year: US equity at 35 against 32 percent, returning 19.8 against 21.0; non-US equity 21 against 23, returning 9.1 against 10.4; fixed income 26 against 27, returning 3.9 against 3.1; real assets and private equity at their policy weights. The fund returned 11.07 percent and the benchmark 11.60. Under the Brinson-Fachler method, allocation contributed plus 0.39, most of it from the US overweight, selection minus 0.91 and interaction minus 0.02. Fixed income was the only segment where managers added value, 0.22. Private equity's shortfall of 0.35 is examined separately, because its benchmark, public equity plus a premium, is compared with lagged valuations.
How a GF570 Unit 8 example is structured
Up front sit the headline result and the method, with the reason Brinson-Fachler was chosen: it measures each allocation decision against the total benchmark return, so an overweight in a segment that beat the whole benchmark earns credit even if the segment's own return was modest. The data table follows, then the effects computed segment by segment with each formula written once. A reconciliation line confirms that the three effects sum to the active return exactly. Interpretation takes the effects in order of size. Selection is examined by segment and manager, allocation by asking whether each weight difference was a decision or drift, and the private equity line gets its own paragraph on benchmark lag. A short comparison shows how the Brinson-Hood-Beebower version would redistribute the same total allocation effect across segments.
Why Brinson-Fachler
Measuring each overweight against the total benchmark return rewards tilting toward segments that beat the whole portfolio, and the analysis explains that choice before any number appears.
Effects that reconcile
Allocation of plus 0.39, selection of minus 0.91 and interaction of minus 0.02 sum to the minus 0.53 active return, shown on one line.
Decision or drift
The US overweight that produced 0.28 of the allocation effect came mostly from market movement, and the analysis says so rather than crediting the committee.
Managers by segment
Equity managers trailed in both regions, 0.38 in the US and 0.30 abroad, while fixed income added 0.22, and each result is tied to a named sleeve.
A benchmark that lags
Private equity's minus 0.35 reflects a public-plus-premium benchmark set against valuations reported a quarter late, and the paper treats it as provisional.
Same total, different map
Under Brinson-Hood-Beebower the US line would show 0.63 and non-US minus 0.21, and the comparison explains why the segment picture shifts while the total holds.
Where marks go in GF570 Unit 8
Attribution analyses lose most when the effects fail to sum to the active return, since the reconciliation is the check a grader runs first. Effects reported for the total fund without a segment breakdown answer only half the question. Papers that credit the committee for an allocation effect produced by market drift overstate skill, and graders at this level expect the difference to be named. Interaction is often dropped or folded silently into selection without saying which convention was used. Private equity compared with a public benchmark and no mention of lagged valuations draws comment, because timing alone can manufacture a large selection figure. Concluding that the managers failed, on a single year and without noting how little one year can show, generally scores below a verdict that is qualified.
Get a GF570 Unit 8 example written to your instructions
Segment weights and returns from your GF570 Unit 8 data, the benchmark's definition and the rubric suffice; say which attribution method your text uses. Effects are computed per segment, reconciled to the active return and interpreted decision by decision. The opening custom sample is ready inside 24-48h, with no charge attached.
GF570 Unit 8 questions, answered
Which attribution method should I use?
The one your text teaches, named at the start. Brinson-Fachler and Brinson-Hood-Beebower give the same total allocation effect but distribute it differently across segments. The sample uses Brinson-Fachler and shows the alternative in a short comparison, so a grader expecting either method can follow the reasoning and see that the totals agree.
What is the interaction effect?
The part of active return that comes from overweighting a segment where the manager also outperformed, or underweighting one where the manager lagged. It is the product of the weight difference and the return difference. Some texts fold it into selection. The sample keeps it as its own line, here a small minus 0.02, and states the convention it follows.
Should private equity be in the attribution at all?
Usually yes, with a caution. Its benchmark is often a public index plus a premium, while its returns arrive on valuations reported with a lag, so one year's comparison can mislead. The sample includes the segment, flags the lag, and suggests judging private equity over longer periods with a method suited to irregular cash flows.