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Hidden Risks in Mean-Variance Optimization: An Integrated-Risk Asset Allocation Proposal

In: Interest Rate Models, Asset Allocation and Quantitative Techniques for Central Banks and Sovereign Wealth Funds

Author

Listed:
  • José Luiz Barros Fernandes
  • José Renato Haas Ornelas

Abstract

The traditional mean—variance asset allocation approach (Markowitz 1952) considers the volatility of returns as the only risk factor. However, investors are usually concerned about other types of risk or negative statistical properties of returns. For instance, investors usually care about credit and liquidity risks, and the skewness and kurtosis of returns. Thus, there is a risk premium embedded in their returns to compensate for additional risk taking. If those risk premia are not taken into account in the analysis, the results of the model tend to be distorted, with portfolios carrying these hidden risks dominating the risk-free portfolios. Moreover, the resulting portfolios for the traditional model tend to be badly behaved due to the overconfidence on the risk/return estimation. Black and Litterman (1992) realize that quantitative asset allocation models have not played the important role they should in global portfolio management, partly due to the previous problems.

Suggested Citation

  • José Luiz Barros Fernandes & José Renato Haas Ornelas, 2010. "Hidden Risks in Mean-Variance Optimization: An Integrated-Risk Asset Allocation Proposal," Palgrave Macmillan Books, in: Arjan B. Berkelaar & Joachim Coche & Ken Nyholm (ed.), Interest Rate Models, Asset Allocation and Quantitative Techniques for Central Banks and Sovereign Wealth Funds, chapter 6, pages 112-133, Palgrave Macmillan.
    • Handle: RePEc:pal:palchp:978-0-230-25129-8_6
    DOI: 10.1057/9780230251298_6
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    Cited by:

    1. Jukka Pihlman & Han van der Hoorn, 2010. "Procyclicality in Central Bank Reserve Management: Evidence from the Crisis," IMF Working Papers 2010/150, International Monetary Fund.

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