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Robust risk budgeting

Author

Listed:
  • Michalis Kapsos

    (Imperial College of Science, Technology and Medicine)

  • Nicos Christofides

    (Imperial College of Science, Technology and Medicine)

  • Berc Rustem

    (Imperial College of Science, Technology and Medicine)

Abstract

Risk based portfolio construction and particular risk parity or equally weighted risk contribution became popular among practitioners. These approaches focus only on risk and are agnostic with respect to the expected returns. In this paper, we consider risk budgeting; a generalization of risk parity. We propose an alternative formulation that is more efficient computationally. We introduce the robust risk budgeting, a robust variant of the standard risk budgeting that deals with the uncertainty in the input parameters. We show that the problem remains tractable under different types of uncertainty. We evaluate the proposed framework on real data and we observe a positive premium associated with the robust variant.

Suggested Citation

  • Michalis Kapsos & Nicos Christofides & Berc Rustem, 2018. "Robust risk budgeting," Annals of Operations Research, Springer, vol. 266(1), pages 199-221, July.
    • Handle: RePEc:spr:annopr:v:266:y:2018:i:1:d:10.1007_s10479-017-2469-4
    DOI: 10.1007/s10479-017-2469-4
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    References listed on IDEAS

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    1. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    2. Roncalli, Thierry, 2013. "Introduction to Risk Parity and Budgeting," MPRA Paper 47679, University Library of Munich, Germany.
    3. Victor DeMiguel & Lorenzo Garlappi & Francisco J. Nogales & Raman Uppal, 2009. "A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms," Management Science, INFORMS, vol. 55(5), pages 798-812, May.
    4. Merton, Robert C., 1980. "On estimating the expected return on the market : An exploratory investigation," Journal of Financial Economics, Elsevier, vol. 8(4), pages 323-361, December.
    5. R. Rockafellar & Stan Uryasev & Michael Zabarankin, 2006. "Generalized deviations in risk analysis," Finance and Stochastics, Springer, vol. 10(1), pages 51-74, January.
    6. Kapsos, Michalis & Christofides, Nicos & Rustem, Berç, 2014. "Worst-case robust Omega ratio," European Journal of Operational Research, Elsevier, vol. 234(2), pages 499-507.
    7. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    8. Bekaert, Geert & Wu, Guojun, 2000. "Asymmetric Volatility and Risk in Equity Markets," The Review of Financial Studies, Society for Financial Studies, vol. 13(1), pages 1-42.
    9. R.H. Tütüncü & M. Koenig, 2004. "Robust Asset Allocation," Annals of Operations Research, Springer, vol. 132(1), pages 157-187, November.
    10. Stanislav Žaković & Berc Rustem, 2003. "Semi-Infinite Programming and Applications to Minimax Problems," Annals of Operations Research, Springer, vol. 124(1), pages 81-110, November.
    11. Shushang Zhu & Masao Fukushima, 2009. "Worst-Case Conditional Value-at-Risk with Application to Robust Portfolio Management," Operations Research, INFORMS, vol. 57(5), pages 1155-1168, October.
    12. Bruder, Benjamin & Roncalli, Thierry, 2012. "Managing risk exposures using the risk budgeting approach," MPRA Paper 37246, University Library of Munich, Germany.
    13. repec:dau:papers:123456789/4688 is not listed on IDEAS
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    Cited by:

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    2. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2022. "Robust portfolio selection problems: a comprehensive review," Operational Research, Springer, vol. 22(4), pages 3203-3264, September.
    3. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    4. Giorgio Costa & Roy Kwon, 2020. "A robust framework for risk parity portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 21(5), pages 447-466, September.
    5. M. Bayat & F. Hooshmand & S. A. MirHassani, 2024. "Scenario-based stochastic model and efficient cross-entropy algorithm for the risk-budgeting problem," Annals of Operations Research, Springer, vol. 341(2), pages 731-755, October.
    6. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2021. "Robust Portfolio Selection Problems: A Comprehensive Review," Papers 2103.13806, arXiv.org, revised Jan 2022.

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