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Mitigating Estimation Risk in Asset Allocation: Diagonal Models Versus 1/ N Diversification
Author(s) -
Stivers Chris,
Sun Licheng
Publication year - 2016
Publication title -
financial review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.621
H-Index - 47
eISSN - 1540-6288
pISSN - 0732-8516
DOI - 10.1111/fire.12108
Subject(s) - diversification (marketing strategy) , volatility (finance) , econometrics , diagonal , asset allocation , economics , asset (computer security) , covariance matrix , estimation , computer science , mathematics , financial economics , statistics , business , portfolio , geometry , computer security , management , marketing
Recent literature suggests that optimal asset‐allocation models struggle to consistently outperform the 1/ N naïve diversification strategy, which highlights estimation‐risk concerns. We propose a dichotomous classification of asset‐allocation models based on which elements of the inverse covariance matrix that a model uses: diagonal only versus full matrix. We argue that parsimonious diagonal‐only strategies, which use limited information such as volatility or idiosyncratic volatility, are likely to offer a good tradeoff between incorporating limited information while mitigating estimation risk. Evaluating five sets of portfolios over 1926–2012, we find that 1/ N is generally not optimal when compared with these diagonal strategies.