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DIVERSIFICATION STRATEGIES: DO LIMITED DATA CONSTRAIN INVESTORS?
Author(s) -
Murtazashvili Irina,
Vozlyublennaia Nadia
Publication year - 2013
Publication title -
journal of financial research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.319
H-Index - 49
eISSN - 1475-6803
pISSN - 0270-2592
DOI - 10.1111/j.1475-6803.2013.12008.x
Subject(s) - diversification (marketing strategy) , portfolio optimization , portfolio , econometrics , asset allocation , variance (accounting) , covariance matrix , covariance , earnings , asset (computer security) , sharpe ratio , economics , statistics , computer science , financial economics , mathematics , business , finance , accounting , marketing , computer security
We demonstrate that the mean–variance optimal portfolio does not outperform (out of sample) the naive 1/ N diversification strategy even if securities are grouped into indexes or broad asset classes. This finding is due to insufficient data on past returns, which limit investors' ability to accurately estimate the means and covariance structure of securities. The resulting high estimation errors eliminate the benefits of using the means and covariance matrix as compared to the naive strategy in portfolio optimization. Using value‐weighted indexes, characteristic‐sorted portfolios, or portfolios defined by principal components as underlying assets in mean–variance optimization does not help. At the same time, increasing data frequency or adding data on past earnings may in some cases make mean–variance optimization useful.