Quantile Connectedness: Modelling Tail Behaviour in Financial Networks

This website provides additional interactive resources to accompany the research paper Quantile Connectedness: Modelling Tail Behaviour in the Topology of Financial Networks by Tomohiro Ando, Matthew Greenwood-Nimmo and Yongcheol Shin

The paper is part of an Australian Research Council funded project on credit risk transmission in the global economy

The paper develops a new framework to study how the structure of a financial network changes with the size of the shocks that affect the network

Our technique employs a new type of VAR model which is estimated by quantile regression under the assumption that the cross-section correlation in the disturbance terms is driven by a finite number of observed common factors

We use our model to demonstrate that large credit risk shocks propagate through the global financial system differently than small shocks

Under the Network Visualisations tab we provide several graphical illustrations of the extent of quantile-variation in the structure of the credit risk network between January 2006 and July 2015

Under the Methodology tab we provide a sketch of the estimation methodology

Under the Dataset tab we describe the data used to construct the network

Under the About Us tab you can find links to our instutional and personal websites

Please note that this is a preliminary working version of the website and its content is subject to change without notice