Template-Type: ReDIF-Paper 1.0
Series: Tinbergen Institute Discussion Papers
Creation-Date: 2021-05-10
Number: 21-040/III
Author-Name: Igor Custodio João
Author-Workplace-Name: Vrije Universiteit Amsterdam
Author-Name: Andre Lucas
Author-Workplace-Name: Vrije Universiteit Amsterdam
Author-Name: Julia Schaumburg
Author-Workplace-Name: Vrije Universiteit Amsterdam
Title: Clustering Dynamics and Persistence for Financial Multivariate Panel Data
Abstract: We introduce a new method for dynamic clustering of panel data with dynamics for cluster location and shape, cluster composition, and for the number of clusters. Whereas current techniques typically result in (economically) too many switches, our method results in economically more meaningful dynamic clustering patterns. It does so by extending standard cross-sectional clustering techniques using shrinkage towards previous cluster means. In this way, the different cross-sections in the panel are tied together, substantially reducing short-lived switches of units between clusters (flickering) and the birth and death of incidental, economically less meaningful clusters. In a Monte Carlo simulation, we study how to set the penalty parameter in a data-driven way. A systemic risk surveillance example for business model classification in the global insurance industry illustrates how the new method works empirically.	
Classification-JEL: G22, C33, C38
Keywords: dynamic clustering, shrinkage, cluster membership persistence, Silhouette index, insurance
File-URL: https://papers.tinbergen.nl/21040.pdf
File-Format: application/pdf
File-Size: 1145118 bytes
Handle: RePEc:tin:wpaper:20210040