A novel multivariate copula of Raftery type with multiple dependence parameters and its neutrosophic application in finance

Abstract

This paper introduces an innovative multivariate exponential distribution, specifically of Raftery type, characterized by heterogeneous dependence parameters. Various properties of this distribution family are thoroughly investigated, with particular emphasis placed on the copula derived from this model. Notably, this copula is non-exchangeable and demonstrates multiple dependence parameters. Different properties associated with this novel copula, including the examination of estimation parameters, have been thoroughly investigated. The efficacy of the proposed copula is demonstrated through its successful application in modeling a real neutrosophic dataset associated with the New York and American Stock Exchanges.