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dc.contributor.authorLing, A.
dc.contributor.authorSun, Jie
dc.contributor.authorYang, X.
dc.identifier.citationLing, 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.

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.

dc.publisherElsevier BV
dc.titleRobust tracking error portfolio selection with worst-case downside risk measures
dc.typeJournal Article
dcterms.source.titleJournal of Economic Dynamics and Control
curtin.accessStatusFulltext not available

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