A review of two decades of correlations, hierarchies, networks and clustering in financial markets
We review the state of the art of clustering financial time series and the study of their
correlations alongside other interaction networks. The aim of the review is to gather in one …
correlations alongside other interaction networks. The aim of the review is to gather in one …
Trimmed fuzzy clustering of financial time series based on dynamic time warping
P D'Urso, L De Giovanni, R Massari - Annals of operations research, 2021 - Springer
In finance, cluster analysis is a tool particularly useful for classifying stock market
multivariate time series data related to daily returns, volatility daily stocks returns, commodity …
multivariate time series data related to daily returns, volatility daily stocks returns, commodity …
Tail-risk spillovers from China to G7 stock market returns during the COVID-19 outbreak: A market and sectoral analysis
This study uses a combination of copulas and CoVaR to investigate risk spillovers from
China to G7 countries before and during the COVID-19 pandemic. Using daily data on stock …
China to G7 countries before and during the COVID-19 pandemic. Using daily data on stock …
[HTML][HTML] Quantile-based fuzzy clustering of multivariate time series in the frequency domain
Á López-Oriona, JA Vilar, P D'Urso - Fuzzy Sets and Systems, 2022 - Elsevier
A novel procedure to perform fuzzy clustering of multivariate time series generated from
different dependence models is proposed. Different amounts of dissimilarity between the …
different dependence models is proposed. Different amounts of dissimilarity between the …
Hierarchical time series clustering on tail dependence with linkage based on a multivariate copula approach
G De Luca, P Zuccolotto - International Journal of Approximate Reasoning, 2021 - Elsevier
Time series clustering with a dissimilarity matrix based on tail dependence coefficients
estimated by copula functions has been proposed in 2011 by De Luca and Zuccolotto, who …
estimated by copula functions has been proposed in 2011 by De Luca and Zuccolotto, who …
Copula-based fuzzy clustering of spatial time series
This paper contributes to the existing literature on the analysis of spatial time series
presenting a new clustering algorithm called COFUST, ie COpula-based FUzzy clustering …
presenting a new clustering algorithm called COFUST, ie COpula-based FUzzy clustering …
The devil Is in the tail dependence: an assessment of multivariate copula‐based frameworks and dependence concepts for coastal compound flood dynamics
A hurricane event can often produce both intense rainfall and a storm tide that can cause a
major compound flooding threat to coastlines. This paper examined applications of …
major compound flooding threat to coastlines. This paper examined applications of …
A spatially‐weighted AMH copula‐based dissimilarity measure for clustering variables: An application to urban thermal efficiency
Investigating thermal energy demand is crucial for developing sustainable cities and the
efficient use of renewable sources. Despite the advances made in this field, the analysis of …
efficient use of renewable sources. Despite the advances made in this field, the analysis of …
[HTML][HTML] Dissimilarity functions for rank-invariant hierarchical clustering of continuous variables
A theoretical framework is presented for a (copula-based) notion of dissimilarity between
continuous random vectors and its main properties are studied. The proposed dissimilarity …
continuous random vectors and its main properties are studied. The proposed dissimilarity …
Copulas, diagonals, and tail dependence
We present some known and novel aspects about bivariate copulas with prescribed
diagonal section by highlighting their use in the description of the tail dependence …
diagonal section by highlighting their use in the description of the tail dependence …