Quantile connectedness: modelling tail behaviour in the topology of financial networks

PLEASE NOTE: THIS EVENT HAS BEEN CANCELLED
Crawford School of Public Policy | Centre for Applied Macroeconomic Analysis

Event details

Seminar

Date & time

Thursday 25 July 2019
11.00am–12.00pm

Venue

Seminar Room 2, Crawford School of Public Policy, 132 Lennox Crossing, ANU

Speaker

Matthew Greenwood-Nimmo, University of Melbourne

Contacts

Rossana Bastos Pinto
61 2 61258108

In this seminar, the author will present his paper on ‘Quantile connectedness: Modelling tail behaviour in the topology of financial networks’ where he develops a new technique to estimate vector autoregressions by quantile regression. A factor structure is used to remove cross-section correlation in the residuals such that the system can be estimated on an equation-by-equation basis using existing quantile regression toolboxes.

The author uses his model to study credit risk spillovers among a panel of 18 sovereigns and their respective financial sectors between January 2006 and February 2012. He shows that idiosyncratic credit risk shocks do not propagate strongly at the median but that powerful spillovers occur in both tails. Furthermore, rolling sample analysis reveals marked time-varying tail-dependence. These important features of credit risk transmission are obscured in models estimated using conventional conditional mean estimators.

Matthew Greenwood-Nimmo is a Senior Lecturer in Economics at the University of Melbourne. His primary research areas are macroeconometrics and financial econometrics. His current work focuses on the econometric analysis of networks and the estimation and interpretation of high-dimensional econometric models.

The CAMA Macroeconomics Brown Bag Seminars offer CAMA speakers, in particular PhD students, an opportunity to present their work in progress in front of their peers, and reputable visitors to showcase their work.

Updated:  9 December 2019/Responsible Officer:  Crawford Engagement/Page Contact:  CAP Web Team