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    Robust tracking error portfolio selection with worst-case downside risk measures

    Access Status
    Fulltext not available
    Authors
    Ling, A.
    Sun, Jie
    Yang, X.
    Date
    2014
    Type
    Journal Article
    
    Metadata
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    Citation
    Ling, Aifan and Sun, Jie and Yang, Xiaoguang. 2014. Robust tracking error portfolio selection with worst-case downside risk measures. Journal of Economic Dynamics and Control. 39: pp. 178-207.
    Source Title
    Journal of Economic Dynamics and Control
    DOI
    10.1016/j.jedc.2013.11.011
    ISSN
    01651889
    URI
    http://hdl.handle.net/20.500.11937/11097
    Collection
    • Curtin Research Publications
    Abstract

    This paper proposes downside risk measure models in portfolio selection that captures uncertainties both in distribution and in parameters. The worst-case distribution with given information on the mean value and the covariance matrix is used, together with ellipsoidal and polytopic uncertainty sets, to build-up this type of downside risk model. As an application of the models, the tracking error portfolio selection problem is considered. By lifting the vector variables to positive semidefinite matrix variables, we obtain semidefinite programming formulations of the robust tracking portfolio models. Numerical results are presented in tracking SSE50 of the Shanghai Stock Exchange. Compared with the tracking error variance portfolio model and the equally weighted strategy, the proposed models are more stable, have better accumulated wealth and have much better Sharpe ratio in the investment period for the majority of observed instances.

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