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Mean-value at risk portfolio efficiency: approaches based on data envelopment analysis models with negative data and their empirical behaviour

Publication at Faculty of Mathematics and Physics |
2016

Abstract

We deal with the problem of an investor who is using a mean-risk model for accessing efficiency of investment opportunities. Our investor employs value at risk on several risk levels at the same time which corresponds to the approach called risk shaping.

We review several data envelopment analysis (DEA) models which can deal with negative data. We show that a diversification-consistent extension of the DEA models based on a directional distance measure can be used to identify the Pareto-Koopmans efficient investment opportunities.

We derive reformulations as chance constrained, nonlinear and mixed-integer problems under particular assumptions. In the numerical study, we access efficiency of US industry representative portfolios based on empirical distribution of random returns.

We employ bootstrap and jackknife to investigate the empirical properties of the efficiency estimators.