
Explanation:
Option B is correct. Empirical studies and theoretical models show that there is a proportional relationship between a portfolio manager's tracking error and portfolio return dispersion. Higher active risk (tracking error) leads to wider potential deviations in the specific weights held in different accounts, increasing dispersion.
Option A is incorrect. Dual-benchmark optimization is highly restrictive and typically leads to constrained portfolios that may not necessarily achieve higher average returns. Option C is incorrect. Dispersion is driven by both client-specific constraints (e.g., tax situations, specific restrictions, timing of cash flows) and manager-driven factors (e.g., trade execution delays across accounts, block trade allocation). Therefore, it is not purely client-driven. Option D is incorrect. Reducing dispersion to absolute zero is neither practical nor recommended. Clients possess individual risk tolerances, cash flow needs, and constraints, which inherently warrant some level of acceptable dispersion.
Ultimate access to all questions.
No comments yet.
A
Dual-benchmark optimization can reduce dispersion and help achieve higher average returns.
B
A portfolio manager’s tracking error and dispersion tend to be proportional to each other over time.
C
Dispersion is always client-driven since it refers to the variance in the performances of client portfolios managed by the same manager.
D
Portfolio managers can control dispersion and should aim to reduce any existing dispersion to zero.