Why is my allocation effect NEGATIVE for a sector that had positive returns?

Short answer: the allocation effect sign depends on TWO things at once — whether you overweighted or underweighted the sector AND whether the sector beat the OVERALL benchmark. Technology returned 10.10% (good in absolute terms), but if your portfolio UNDERWEIGHTED Technology while Technology was beating the overall benchmark, you DID miss out — and the allocation effect correctly captures that as negative.

The Brinson-Fachler allocation formula

Your Technology example

Plug in:

• $P_w = 35\%$, $B_w = 40\%$ → $(P_w - B_w) = (0.35 - 0.40) = -0.05$ (UNDERWEIGHT)
• $R_{B,\text{Tech}} = 10.10\%$, $R_{B,\text{total}} \approx 6.00\%$ → $(R_{B,\text{sector}} - R_{B,\text{total}}) = (0.1010 - 0.0600) = +0.041$ (Tech beat total)

(The exact −0.505% number you see comes from a slightly different $R_{B,\text{total}}$ assumption — the point is the SIGN.)

What it is telling you

The allocation effect says: "You bet wrong on how much capital to put in Tech." Tech was a winning sector, you underweighted it, you cost yourself relative return. The selection effect (which IS positive at +0.44% in your table) tells a different story: "Within whatever Tech you DID own, you picked good stocks." Those are two separate decisions, and Brinson correctly grades them separately.

Mental model: four allocation outcomes

Two ways to get a POSITIVE allocation: overweight a winner OR correctly avoid (underweight) a loser. Two ways to get NEGATIVE: overweight a loser OR underweight a winner.

The trap on exam questions

When a question asks "which sector had the optimal decision," it is looking for BOTH allocation AND selection to be positive. The Tech row in your table has positive selection but negative allocation → NOT optimal. Look for rows where both columns have the same positive sign.

See more on the full attribution mechanic in our Brinson attribution article.