Network mining based elucidation of the dynamics of cross-market clustering and connectedness in Asian region: An MST and hierarchical clustering approach

• Main Authors: Biplab Bhattacharjee, Muhammad Shafi, Animesh Acharjee
• Format: Article
• Language: English
• Published: Elsevier 2019-04-01
• Series: Journal of King Saud University: Computer and Information Sciences
• Online Access: http://www.sciencedirect.com/science/article/pii/S1319157817302343

We investigate the dynamics of cross-market clustering and connectedness of the Asian capital markets in this study. We perform the cross-correlation structure analysis of the daily return data of 14 global indices belonging to the major Asian capital markets by using the sub-dominant ultrametric distance based MST and Hierarchical Clustering techniques. The study dataset is for fourteen years duration (2002–2016). A rolling window approach is used to generate 151 temporally synchronous observations. We generate MSTs and Hierarchical Clustering plots (based on average linkage distance) for these temporally synchronous observations, and visually comprehend them to decipher the cross-market cluster formation, hub node formation, and connectivity structure with hub nodes. To identify those set of Asian markets having close connectivity with India, we employed a weighted hop count method and based on its scorings the Asian indices are subsequently ranked. We also investigate the influence of the 2008 financial crisis on the connectivity and clustering patterns in the Asian indices network. We also compute the key network topological parameters to decipher the dynamically varying topological properties, and with a particular reference during financial crisis periods. Keywords: Network filtering, Data mining, Applied Graph Theory, Financial network analysis, MST, Hierarchical Clustering