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FRM Part II · FRM Exam Part II · Portfolio Construction

A risk manager compares unconstrained mean-variance optimization using sample mean returns with Black-Litterman optimization. Which statement best explains why Black-Litterman typically produces more stable, diversified portfolios?

Black-Litterman is more stable because it anchors expected returns on equilibrium values and modifies them only through confidence-weighted views, with effects flowing through the covariance matrix. This limits the extreme, error-maximizing weights typical of optimization based on noisy sample means.

  1. AIt eliminates estimation error by assuming returns are known with certainty
  2. BIt anchors expected returns on equilibrium values and adjusts only those assets on which views are expressed, with the adjustment scaled by confidence, spreading effects through the covariance matrixCorrect
  3. CIt imposes a no-short-sales constraint by construction
  4. DIt replaces the covariance matrix with an identity matrix

Explanation

Sample means are noisy, and optimizers magnify errors into extreme weights. Black-Litterman starts from equilibrium, blends views by confidence, and propagates them through covariances, producing intuitive moderate tilts. It does not remove uncertainty, impose constraints automatically, or alter the covariance matrix to identity.

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