• 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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