Markowitz vs. 1/N: Portfolio Performance, Estimation Errors, and Subjectivity

TY - UNPB

T1 - Markowitz vs. 1/N: Portfolio Performance, Estimation Errors, and Subjectivity

AU - Cheung, Wing

PY - 2024

Y1 - 2024

N2 - This paper reconciles the ‘mean-variance (MV) vs equal-weighting (1/N)’ performance debate using an unbiased performance-to-error map and delineates thresholds where subjective interventions become essential to surpass MV optimisation. Traditional evaluations often yield inconclusive or contradictory results due to a ‘joint-test’ problem entangled with alpha and risk models. We introduce a methodology that isolates portfolio selection, through which we objectively assess performance sensitivity to estimation errors, identify when MV becomes suboptimal, and explore why appropriate subjectivity can enhance performance beyond MV. These findings underscore the importance of structurally incorporating subjectivity and rational investor behaviours into portfolio theory and practice.

AB - This paper reconciles the ‘mean-variance (MV) vs equal-weighting (1/N)’ performance debate using an unbiased performance-to-error map and delineates thresholds where subjective interventions become essential to surpass MV optimisation. Traditional evaluations often yield inconclusive or contradictory results due to a ‘joint-test’ problem entangled with alpha and risk models. We introduce a methodology that isolates portfolio selection, through which we objectively assess performance sensitivity to estimation errors, identify when MV becomes suboptimal, and explore why appropriate subjectivity can enhance performance beyond MV. These findings underscore the importance of structurally incorporating subjectivity and rational investor behaviours into portfolio theory and practice.

M3 - Working paper

BT - Markowitz vs. 1/N: Portfolio Performance, Estimation Errors, and Subjectivity

PB - SSRN

ER -