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On the robustness of risk-based asset allocations

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  • Thorsten Poddig
  • Albina Unger

Abstract

Since the subprime crisis, portfolios based on risk diversification are of great interest to both academic researchers and market practitioners. They have also been employed by several asset management firms and their performance appears promising. Since they do not rely on estimates of expected returns, they are assumed to be robust. The same argument holds for minimum variance and equally weighted portfolios. In this paper, we consider a Monte Carlo simulation, as well as an empirical global portfolio dataset, to study the effect of estimation errors on the outcomes of two recently proposed asset allocations, the equally weighted risk contribution (ERC) and the principal component analysis (PCA) portfolio. The ERC portfolio is more robust to changes in the input parameters and has a smaller estimation error than the Markowitz approaches, whereas the PCA portfolio is even more unstable than the classical approaches. In the worst-case scenario, neither approach delivers what it promises. However, in every case the resulting return–risk relationship is dominated by the Markowitz approaches. Copyright Swiss Society for Financial Market Research 2012

Suggested Citation

  • Thorsten Poddig & Albina Unger, 2012. "On the robustness of risk-based asset allocations," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(3), pages 369-401, September.
    • Handle: RePEc:kap:fmktpm:v:26:y:2012:i:3:p:369-401
    DOI: 10.1007/s11408-012-0190-5
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    References listed on IDEAS

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    Cited by:

    1. M. Hossein Partovi, 2013. "Hedging and Leveraging: Principal Portfolios of the Capital Asset Pricing Model," Papers 1306.4958, arXiv.org.
    2. Hidehiko Shimizu & Takayuki Shiohama, 2019. "Multifactor Portfolio Construction by Factor Risk Parity Strategies: An Empirical Comparison of Global Stock Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(4), pages 453-477, December.
    3. Gilles Boevi Koumou, 2023. "Risk budgeting using a generalized diversity index," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 443-458, October.
    4. Yusuke Uchiyama & Kei Nakagawa, 2022. "Schr\"{o}dinger Risk Diversification Portfolio," Papers 2202.09939, arXiv.org.
    5. Vaughn Gambeta & Roy Kwon, 2020. "Risk Return Trade-Off in Relaxed Risk Parity Portfolio Optimization," JRFM, MDPI, vol. 13(10), pages 1-28, October.
    6. M. Hossein Partovi, 2013. "Hedging and Leveraging: Principal Portfolios of the Capital Asset Pricing Model," Economics Bulletin, AccessEcon, vol. 33(4), pages 2930-2937.

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    More about this item

    Keywords

    Asset allocation; Risk contributions; Minimum variance; Portfolio diversification; Principal component portfolios; Maximum entropy; Naive portfolios; Estimation error; C13; C15; C61; G11;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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