[2O1-J-13] AI application: dynamics in finance

[2O1-J-13-03] Analysis of Inter-bank Network's Temporal Change Using Clustering Structure Change Detection

〇Yuta Niki¹, Kiyoshi Izumi¹, Hiroyasu Matsushima¹, Hiroki Sakaji¹, Takashi Shimada¹ (1. School of Engineering, The University of Tokyo)

Keywords:inter-bank network, clustering structure change detection

In this research, a clustering structure change detection method is employed for analyzing temporal changes of the inter-bank network. The inter-bank network is constructed from data of Italian deposit trading system e-MID, and changes in the structure of the network that focused on the type of the bank are analyzed. By using clustering structure change detection, the change of the inter-bank network's structure after Lehman shock is detected, which depends on the type of bank.