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

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.