Search
Now showing items 1-7 of 7
-
A portfolio diversification strategy via tail dependence clustering
(Springer International Publishing, 2017)We provide a two-stage portfolio selection procedure in order to increase the diversification benefits in a bear market. By exploiting tail dependence-based risky measures, a cluster analysis is carried out for discerning ... -
A multivariate analysis of tourists' spending behaviour
(Springer International Publishing, 2017)According to the micro-economic theories regarding consumption behaviour, the determinants affecting the joint propensity of purchasing different goods and services are investigated. For this purpose, a copula-based model ... -
A multivariate nonlinear analysis of tourism expenditures
(Italian Economic Association, 2013)Independence among different tourism expenditure categories is the most convenient hypothesis for modeling decision–making processes. Nevertheless, the best-suited framework would require dependence among expenditures in ... -
Connectedness measures of spatial contagion in the banking and insurance sector
(Springer International Publishing, 2015)We present some connectedness measures for an economic system that are derived from the spatial contagion measure. These measures are calculated directly from time series data and do not require any parametric assumption. ... -
A test for truncation invariant dependence
(Springer, 2017)A test is proposed to check whether a random sample comes from a truncation invariant copula C, that is, if C is the copula of a pair (U, V) of random variables uniformly distributed on [0, 1], then C is also the copula ... -
Evolution of the dependence of residual lifetimes
(Springer, 2013)We investigate the dependence properties of a vector of residual lifetimes by means of the copula associated with the conditional distribution function. In particular, the evolution of positive dependence properties (like ... -
Cluster analysis of time series via Kendall distribution
(Springer, 2015)We present a method to cluster time series according to the calculation of the pairwise Kendall distribution function between them. A case study with environmental data illustrates the introduced methodology.
