Time series clustering and classification by the autoregressive metric
Computational Statistics & Data Analysis
Clustering heteroskedastic time series by model-based procedures
Computational Statistics & Data Analysis
Hierarchical structure of the German stock market
Expert Systems with Applications: An International Journal
Computational Statistics & Data Analysis
Spatial contagion between financial markets: a copula-based approach
Applied Stochastic Models in Business and Industry
A review of copula models for economic time series
Journal of Multivariate Analysis
Stock market co-movement assessment using a three-phase clustering method
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
A novel spatial contagion measure is proposed that is based on the calculation of suitable conditional Spearman's correlations extracted from the financial time series of interest. Algorithms for the numerical estimation of this measure are illustrated, together with a simulation study showing its features in relations with popular families of copulas. Finally, two applications are presented about the use of spatial contagion measure for determining (asymmetric) linkages in the financial systems, and creating clusters of financial time series. In particular, contrarily to previous approaches in the literature, such clusters identify which time series increase their (positive) association when the market is under distress. The presented methodology is also expected to be useful to select a diversified portfolio of asset returns.