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Equally-weighted Risk Contribution Portfolios: an empirical study using expected shortfall

Author

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  • Elisabetta Cagna

    (Symphonia Sgr)

  • Giulio Casuccio

    (Fondaco sgr)

Abstract

The high volatility observed in financial markets during the last crisis prompted renewed interest in designing truly diversified portfolios. One of the most interesting approach proposed by recent literature is the Equally-weighted Risk Contribution strategy (Maillard et al., 2009), usually implemented with standard deviation as risk measure: our paper extends this approach introducing expected shortfall. The expected shortfall risk contributions are computed through a non-parametric approach which aims to reduce the estimation error generated by the historical sample applying a bootstrap resampling procedure. The ex-post performance analysis also accounts for realistic transaction costs. We find superiority of the ERC portfolios, with better Sharpe ratio along with asymmetric performance metrics.

Suggested Citation

  • Elisabetta Cagna & Giulio Casuccio, 2014. "Equally-weighted Risk Contribution Portfolios: an empirical study using expected shortfall," CeRP Working Papers 142, Center for Research on Pensions and Welfare Policies, Turin (Italy).
    • Handle: RePEc:crp:wpaper:142
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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. Bertsimas, Dimitris & Lauprete, Geoffrey J. & Samarov, Alexander, 2004. "Shortfall as a risk measure: properties, optimization and applications," Journal of Economic Dynamics and Control, Elsevier, vol. 28(7), pages 1353-1381, April.
    3. Roncalli, Thierry, 2013. "Introduction to Risk Parity and Budgeting," MPRA Paper 47679, University Library of Munich, Germany.
    4. 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.
    5. Tasche, Dirk, 2002. "Expected shortfall and beyond," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1519-1533, July.
    6. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    7. Green, Richard C & Hollifield, Burton, 1992. "When Will Mean-Variance Efficient Portfolios Be Well Diversified?," Journal of Finance, American Finance Association, vol. 47(5), pages 1785-1809, December.
    8. Dirk Tasche, 2001. "Conditional Expectation as Quantile Derivative," Papers math/0104190, arXiv.org.
    9. Carlo Acerbi & Dirk Tasche, 2002. "Expected Shortfall: A Natural Coherent Alternative to Value at Risk," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 31(2), pages 379-388, July.
    10. Dirk Tasche, 2007. "Capital Allocation to Business Units and Sub-Portfolios: the Euler Principle," Papers 0708.2542, arXiv.org, revised Jun 2008.
    11. Susanne Emmer & Marie Kratz & Dirk Tasche, 2013. "What is the best risk measure in practice? A comparison of standard measures," Papers 1312.1645, arXiv.org, revised Apr 2015.
    12. Carlo Acerbi & Claudio Nordio & Carlo Sirtori, 2001. "Expected Shortfall as a Tool for Financial Risk Management," Papers cond-mat/0102304, arXiv.org.
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