FRM Part II · FRM Exam Part II · Portfolio Construction

A portfolio manager uses mean-variance optimization with historical average returns as direct inputs for 40 assets. The resulting portfolio holds large long and short positions in a few assets and changes sharply when the inputs are slightly revised. Which is the most accurate explanation?

Mean-variance optimization is very sensitive to estimation error in expected returns. The optimizer overweights assets whose returns are overestimated or risks underestimated, producing extreme, unstable positions that change sharply when inputs are revised slightly.

1. AMean-variance optimization is highly sensitive to estimation error in expected returns, and it tends to overweight assets whose inputs are overestimatedCorrect
2. BThe optimizer ignores covariances and therefore concentrates positions in the highest-volatility assets
3. CMean-variance optimization requires returns to be uniform, which fails when assets differ in size
4. DConcentrated positions arise because the optimizer minimizes tracking error rather than total variance