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Downside risk in multiperiod tracking error models

Author

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  • Diana Barro

    ()

  • Elio Canestrelli

Abstract

The recent crisis made it evident that replicating the performance of a benchmark is not a sufficient goal to meet the expectations of usually risk-averse investors. The manager should also consider that the investors are seeking downside protection when the benchmark performs poorly and thus they should integrate a form of downside risk control. We propose a multiperiod double tracking error portfolio model which combines these two goals and provides enough flexibility. In particular, the control of the downside risk is carried out through the presence of a floor benchmark with respect to which we can accept different levels of shortfall. The choice of a proper measure for downside risk leads to different problem formulations and investment strategies which can reflect different attitudes towards risk. The proposed model is tested through a set of out-of-sample rolling simulations in different market conditions. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Diana Barro & Elio Canestrelli, 2014. "Downside risk in multiperiod tracking error models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(2), pages 263-283, June.
  • Handle: RePEc:spr:cejnor:v:22:y:2014:i:2:p:263-283
    DOI: 10.1007/s10100-013-0290-y
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    Cited by:

    1. repec:spr:cejnor:v:26:y:2018:i:1:d:10.1007_s10100-017-0477-8 is not listed on IDEAS
    2. Diana Barro & Elio Canestrelli & Fabio Lanza, 2014. "Volatility vs. downside risk: optimally protecting against drawdowns and maintaining portfolio performance," Working Papers 2014:18, Department of Economics, University of Venice "Ca' Foscari".

    More about this item

    Keywords

    Tracking error; Downside risk; Dynamic portfolio ; Stochastic programming; 91C26; 90C10;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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