Title: MITIGATING ESTIMATION RISK IN ASSET ALLOCATION: DIAGONAL MODELS VERSUS 1/N DIVERSIFICATION
Authors: CHRIS STIVERS, LICHENG SUN
Publication: THE FINANCIAL REVIEW, 2016 (version here)What are the research questions?
In spite of several efforts by researchers to overcome the estimation-risk problem (the use of estimate inputs based on sample information as if they were representative of the true population) which produces the so-called “wacky weights”, DeMiguel, Garlappi and Uppal (2009) present striking evidence that favors a simple 1/N naıve portfolio strategy.
The authors challenge the results by DeMiguel et al. (2009) by studying the following research question:
Are asset allocation models that use “diagonal” elements of the inverse covariance matrix superior to those using the “full” matrix, in addressing the “wacky weights” problem?
Do “diagonal” models outperform the
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