Sensitivity Analysis of the Mixed Tempered Stable Parameters with Implications in Portfolio Optimization

14 Pages Posted: 2 Oct 2017

See all articles by Asmerilda Hitaj

Asmerilda Hitaj

Università degli Studi di Milano-Bicocca - Dipartimento di Statistica e Metodi Quantitativi

Lorenzo Mercuri

University of Milan

Edit Rroji

Polytechnic University of Milan - Department of Mathematics; Department of Statistics and Quantitative Methods University of Milano-Bicocca

Date Written: September 30, 2017

Abstract

This paper investigates the use, in practical financial problems, of the Mixed Tempered Stable distribution both in its univariate and multivariate formulation. In the univariate context, we study the dependence of a given coherent risk measure on the distribution parameters. The latter allows to identify the parameters that seem to have a greater influence on the given measure of risk.

The multivariate Mixed Tempered Stable distribution enters in a portfolio optimization problem built considering a real market dataset of seventeen hedge fund indexes. We combine the flexibility of the multivariate Mixed Tempered Stable distribution, in capturing different tail behaviors, with the ability of the ARMA-GARCH model in capturing the time dependence observed in the data.

Keywords: Mixed Tempered Stable distribution; sensitivity analysis; portfolio optimization

Suggested Citation

Hitaj, Asmerilda and Mercuri, Lorenzo and Rroji, Edit, Sensitivity Analysis of the Mixed Tempered Stable Parameters with Implications in Portfolio Optimization (September 30, 2017). Available at SSRN: https://ssrn.com/abstract=3045856 or http://dx.doi.org/10.2139/ssrn.3045856

Asmerilda Hitaj

Università degli Studi di Milano-Bicocca - Dipartimento di Statistica e Metodi Quantitativi ( email )

Milano, 20126
Italy

Lorenzo Mercuri

University of Milan ( email )

Via Festa del Perdono, 7
Milan, 20122
Italy

Edit Rroji (Contact Author)

Polytechnic University of Milan - Department of Mathematics ( email )

Via Bonardi, 9
Milano, MI 20133
Italy

Department of Statistics and Quantitative Methods University of Milano-Bicocca ( email )

Piazza dell’Ateneo Nuovo 1, 20126 Milano
Milano, 20126
Italy

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