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Multivariate location-scale mixtures of normals and mean-variance-skewness portfolio allocation

Javier Mencia () and Enrique Sentana ()

Journal of Econometrics, 2009, vol. 153, issue 2, 105-121

Abstract: We show that the distribution of any portfolio whose components jointly follow a location-scale mixture of normals can be characterised solely by its mean, variance and skewness. Under this distributional assumption, we derive the mean-variance-skewness frontier in closed form, and show that it can be spanned by three funds. For practical purposes, we derive a standardised distribution, provide analytical expressions for the log-likelihood score and explain how to evaluate the information matrix. Finally, we present an empirical application in which we obtain the mean-variance-skewness frontier generated by the ten Datastream US sectoral indices, and conduct spanning tests.

Keywords: Generalised; hyperbolic; distribution; Maximum; likelihood; Portfolio; frontiers; Sortino; ratio; Spanning; tests; Tail; dependence (search for similar items in EconPapers)
Date: 2009
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Working Paper: Multivariate location-scale mixtures of normals and mean-variance-skewness portfolio allocation (2009) Downloads
Working Paper: Multivariate Location-Scale Mixtures of Normals and Mean-Variance-skewness Portfolio Allocation (2008) Downloads
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Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

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