Portfolio allocation using multivariate variance gamma models

Hitaj, Asmerilda; Mercuri, Lorenzo

doi:10.1007/s11408-012-0202-5

Cited by 17 publications

(8 citation statements)

References 19 publications

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“…To our knowledge, no empirical research exists addressing this question. It is well known that hedge funds are characterized by high skewness and kurtosis, and different empirical analysis have demonstrated that a three or four‐moment portfolio allocation is better than a two‐moment portfolio allocation (see Athayde & Flores, 2002; Jondeau, Poon, & Rockinger, 2007; Martellini & Ziemann, 2010; Hitaj, Martellini, & Zambruno, 2012; Hitaj & Mercuri, 2013b, etc. ).…”

Section: Introductionmentioning

confidence: 99%

Are Smart Beta strategies suitable for hedge fund portfolios?

Hitaj

Zambruno

2016

Rev Financ Econ

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In the equity context different Smart Beta strategies (such as the equally weighted, global minimum variance, equal risk contribution and maximum diversified ratio) have been proposed as alternatives to the capweighted index. These new approaches have attracted the attention of equity managers as different empirical analyses demonstrate the superiority of these strategies with respect to cap-weighted and to strategies that consider only mean and variance. In this paper we focus our attention to hedge fund index portfolios and analyze if the results reported in the equity framework are still valid. We consider hedge fund index and equity portfolios, the approaches used for portfolio selection are the four 'Smart Beta' strategies, mean-variance and meanvariance-skewness. In the two latter approaches the Taylor approximation of a CARA expected utility function and the Polynomial Goal Programing (PGP) have been used. The obtained portfolios are analyzed in the in-sample as well as in the out-of-sample perspectives.

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Section: Introductionmentioning

confidence: 99%

Are Smart Beta strategies suitable for hedge fund portfolios?

Hitaj

Zambruno

2016

Rev Financ Econ

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“…A similar approach has been used in Semeraro () for the construction of a multivariate Variance Gamma distribution starting from the idea that the components in the mixing random vector are Gamma distributed. However, as observed in Mercuri (), Semeraro's model seems to be too restrictive for describing the joint distribution of asset returns. In particular, the sign of the skewness of the marginal distributions determines the sign of the covariance.…”

Section: Introductionmentioning

confidence: 99%

On Properties of the MixedTS Distribution and Its Multivariate Extension

Hitaj

Hubalek

Mercuri

et al. 2018

Int Statistical Rev

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A review of the univariate MixedTS is given and some new results on the asymptotic tail behaviour are derived. The multivariate version of the Mixed Tempered Stable, which is a generalisation of the Normal Variance Mean Mixtures, is discussed. Characteristics of this distribution, its capacity in fitting tails and in capturing dependence structure between components are investigated. We discuss a random number generating procedure and introduce an estimation methodology based on the minimisation of a distance between empirical and theoretical characteristic functions. Asymptotic tail behaviour of the univariate Mixed Tempered Stable is exploited in the estimation procedure in order to obtain a better fitting on tails. Advantages of the multivariate Mixed Tempered Stable distribution are discussed and illustrated via numerical analysis.

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“…The models proposed in literature that incorporate higher moments in portfolio selection are divided into non-parametric (see, among others, Hitaj et al, 2012, and the literature therein) and parametric (see Jondeau et al, 2007). The advantage of using parametric approaches is the reduction of the number of parameters to estimate if we compare them with non-parametric models (see Hitaj and Mercuri, 2013;Jondeau et al, 2007, and references therein). However, when dealing with portfolio returns, we need to tackle with multivariate distributions.…”

Section: Introductionmentioning

confidence: 99%