 The impact of model risk on dynamic portfolio selection under multi-period mean-standard-deviation criterionSpiridon Penev, Pavel V. Shevchenko and Wei Wu European Journal of Operational Research, 2019, vol. 273, issue 2, 772-784 Abstract: We quantify model risk of a financial portfolio whereby a multi-period mean-standard-deviation criterion is used as a selection criterion. In this work, model risk is defined as the loss due to uncertainty of the underlying distribution of the returns of the assets in the portfolio. The uncertainty is measured by the Kullback–Leibler divergence, i.e., the relative entropy. In the worst case scenario, the optimal robust strategy can be obtained in a semi-analytical form as a solution of a system of nonlinear equations. Several numerical results are presented which allow us to compare the performance of this robust strategy with the optimal non-robust strategy. For illustration, we also quantify the model risk associated with an empirical dataset. Keywords: Multivariate statistics; Robust portfolio allocation; Pseudo dynamic programming; Mean-standard-deviation; Kullback–Leibler divergence (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:273:y:2019:i:2:p:772-784 DOI: 10.1016/j.ejor.2018.08.026 Access Statistics for this article European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati More articles in European Journal of Operational Research from Elsevier |
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