Multivariate location-scale mixtures of normals and mean-variance-skewness portfolio allocation
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.
Year of publication: |
2009
|
---|---|
Authors: | Mencía, Javier ; Sentana, Enrique |
Published in: |
Journal of Econometrics. - Elsevier, ISSN 0304-4076. - Vol. 153.2009, 2, p. 105-121
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Publisher: |
Elsevier |
Keywords: | Generalised hyperbolic distribution Maximum likelihood Portfolio frontiers Sortino ratio Spanning tests Tail dependence |
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