In this paper we propose a heuristic strategy aimed at selecting and analysing a set of fi nancial assets, focusing attention on their multivariate tail dependence structure. The selection, obtained through an algorithmic procedure based on data mining tools, assumes the existence of a reference asset we are specifi cally interested to. The procedure allows one to opt for two alternatives: to prefer those assets exhibiting either a minimum lower tail dependence or a maximum upper tail dependence. The former could be a recommendable opportunity in a fi nancial crisis period. For the selected assets, the tail dependence coeffi cients are estimated by means of a proper multivariate copula function.

Combining Random Forest and Copula Function: a heuristic approach for selecting assets in a financial crisis perspective

DE LUCA, GIOVANNI;RIVIECCIO, GIORGIA;
2010

Abstract

In this paper we propose a heuristic strategy aimed at selecting and analysing a set of fi nancial assets, focusing attention on their multivariate tail dependence structure. The selection, obtained through an algorithmic procedure based on data mining tools, assumes the existence of a reference asset we are specifi cally interested to. The procedure allows one to opt for two alternatives: to prefer those assets exhibiting either a minimum lower tail dependence or a maximum upper tail dependence. The former could be a recommendable opportunity in a fi nancial crisis period. For the selected assets, the tail dependence coeffi cients are estimated by means of a proper multivariate copula function.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11367/2303
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