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Superiority of optimized portfolios to naive diversification: Fact or fiction?

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  • Zakamulin, Valeriy

Abstract

DeMiguel, Garlappi, and Uppal (2009) conducted a highly influential study where they demonstrated that none of the optimized portfolios consistently outperformed the naive diversification. This result triggered a heated debate within the academic community on whether portfolio optimization adds value. Nowadays several studies claim to defend the value of portfolio optimization. The commonality in all these studies is that various portfolio optimization methods are implemented using the datasets generously provided by Kenneth French and the performance is measured by means of the Sharpe ratio. This paper aims to provide a cautionary note regarding the use of Kenneth French datasets in portfolio optimization without controlling whether the superior performance appears due to better mean-variance efficiency or due to exposures to established factor premiums. First, we demonstrate that the low-volatility effect is present in virtually all datasets in the Kenneth French online data library. Second, using a few simple portfolio optimization models that are said to outperform the naive diversification, we show that these portfolios are tilted towards assets with lowest volatilities and, after controlling for the low-volatility effect, there is absolutely no evidence of superior performance. The main conclusion that we reach in our paper is that a convincing demonstration of the value of portfolio optimization cannot be made without showing that the superior performance cannot be attributed to profiting from some known anomalies.

Suggested Citation

  • Zakamulin, Valeriy, 2017. "Superiority of optimized portfolios to naive diversification: Fact or fiction?," Finance Research Letters, Elsevier, vol. 22(C), pages 122-128.
  • Handle: RePEc:eee:finlet:v:22:y:2017:i:c:p:122-128
    DOI: 10.1016/j.frl.2016.12.007
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    References listed on IDEAS

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    1. Tu, Jun & Zhou, Guofu, 2011. "Markowitz meets Talmud: A combination of sophisticated and naive diversification strategies," Journal of Financial Economics, Elsevier, vol. 99(1), pages 204-215, January.
    2. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    3. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    4. Zhanhui Chen & Ralitsa Petkova, 2012. "Does Idiosyncratic Volatility Proxy for Risk Exposure?," Review of Financial Studies, Society for Financial Studies, vol. 25(9), pages 2745-2787.
    5. Blitz, David & Pang, Juan & van Vliet, Pim, 2013. "The volatility effect in emerging markets," Emerging Markets Review, Elsevier, vol. 16(C), pages 31-45.
    6. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    7. Jobson, J D & Korkie, Bob M, 1981. "Performance Hypothesis Testing with the Sharpe and Treynor Measures," Journal of Finance, American Finance Association, vol. 36(4), pages 889-908, September.
    8. Guo, Hui & Savickas, Robert, 2010. "Relation between time-series and cross-sectional effects of idiosyncratic variance on stock returns," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1637-1649, July.
    9. Kirby, Chris & Ostdiek, Barbara, 2012. "It’s All in the Timing: Simple Active Portfolio Strategies that Outperform Naïve Diversification," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(2), pages 437-467, April.
    10. Scherer, Bernd, 2011. "A note on the returns from minimum variance investing," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 652-660, September.
    11. Blitz, D.C. & van Vliet, P., 2007. "The Volatility Effect: Lower Risk without Lower Return," ERIM Report Series Research in Management ERS-2007-044-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
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    Cited by:

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    2. Ramesh Adhikari & Kyle J. Putnam & Humnath Panta, 2020. "Robust Optimization-Based Commodity Portfolio Performance," IJFS, MDPI, vol. 8(3), pages 1-16, September.

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    More about this item

    Keywords

    Low-volatility anomaly; Portfolio optimization; Naive diversification; Out-of-sample simulations; Risk-based explanation;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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