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Minimum Variance Portfolio Composition

Authors: Roger Clarke; Harindra de Silva; Steven Thorley;

Minimum Variance Portfolio Composition

Abstract

Empirical studies document that equity portfolios constructed to have the lowest possible risk have surprisingly high average returns. Clarke, de Silva, andThorley derive an analytic solution for the long-only minimum-variance portfolio under the assumption of a single-factor covariance matrix. The equation for optimal security weights has a simple and intuitive form that provides several insights on minimum-variance portfolio composition. While high idiosyncratic risk can lead to a low security weight, high systematic risk takes the large majority of investable securities out of long-only solutions. The relatively small set of securities that remains has market betas below an analytically specified threshold beta. The ratio of portfolio beta to threshold beta dictates the portion of ex ante portfolio variance that is market-factor related. The authors verify and illustrate the portfolio mathematics using historical data on the U.S. equity market and explore how the single-factor analytic results compare to numerical optimization under a generalized covariance matrix. The analytic and empirical results of this study suggest that minimum-variance portfolio performance is largely a function of the long-standing empirical critique of the traditional CAPM that low-beta stocks have relatively high average returns.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
146
Top 1%
Top 1%
Top 10%
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