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A note on the returns from minimum variance investing

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  • Scherer, Bernd
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    Abstract

    Disappointed with the performance of market weighted benchmark portfolios yet skeptical about the merits of active portfolio management, investors in recent years turned to alternative index definitions. Minimum variance investing is one of these popular concepts. I show in this paper that the portfolio construction process behind minimum variance investing implicitly picks up risk-based pricing anomalies. In other words the minimum variance tends to hold low beta and low residual risk stocks. Long/short portfolios based on these characteristics have been associated in the empirical literature with risk adjusted outperformance. This paper shows that 83% of the variation of the minimum variance portfolio excess returns (relative to a capitalization weighted alternative) can be attributed to the FAMA/FRENCH factors as well as to the returns on two characteristic anomaly portfolios. All regression coefficients (factor exposures) are highly significant, stable over the estimation period and correspond remarkably well with our economic intuition. The paper also shows that a direct combination of market weighted benchmark portfolio and risk based characteristic portfolios will provide a statistically significant improvement over the indirect pickup via the minimum variance portfolio.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0927539811000442
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    Article provided by Elsevier in its journal Journal of Empirical Finance.

    Volume (Year): 18 (2011)
    Issue (Month): 4 (September)
    Pages: 652-660

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    Handle: RePEc:eee:empfin:v:18:y:2011:i:4:p:652-660
    Contact details of provider: Web page: http://www.elsevier.com/locate/jempfin

    Keywords: Minimum variance portfolio SHARPE-ratio Risk based anomalies Market capitalization weighted portfolio Bootstrapping;

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    Cited by:

    1. Chiu, Wan-Yi & Jiang, Ching-Hai, 2016. "On the weight sign of the global minimum variance portfolio," Finance Research Letters, Elsevier, vol. 19(C), pages 241-246.
    2. Cazalet, Zelia & Grison, Pierre & Roncalli, Thierry, 2013. "The Smart Beta Indexing Puzzle," MPRA Paper 48823, University Library of Munich, Germany.
    3. Bertrand, Philippe & Lapointe, Vincent, 2015. "How performance of risk-based strategies is modified by socially responsible investment universe?," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 175-190.
    4. Auer, Benjamin R. & Schuhmacher, Frank, 2016. "Do socially (ir)responsible investments pay? New evidence from international ESG data," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 51-62.
    5. Auer, Benjamin R. & Schuhmacher, Frank, 2013. "Performance hypothesis testing with the Sharpe ratio: The case of hedge funds," Finance Research Letters, Elsevier, vol. 10(4), pages 196-208.
    6. Serge Darolles & Christian Gouriéroux & Emmanuelle Jay, 2012. "Robust Portfolio Allocation with Systematic Risk Contribution Restrictions," Working Papers 2012-35, Centre de Recherche en Economie et Statistique.
    7. Sharma, Prateek & Vipul,, 2015. "Performance of risk-based portfolios under different market conditions: Evidence from India," Research in International Business and Finance, Elsevier, vol. 34(C), pages 397-411.
    8. Ardia, David & Boudt, Kris & Wauters, Marjan, 2016. "The economic benefits of market timing the style allocation of characteristic-based portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 38-62.

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