Multiple testing for the topology of financial networks by Professor Richard Luger

Richard Luger is a Professor in the Department of Finance, Insurance and Real Estate at Laval University in Quebec City, Canada. He has previously held positions at the Bank of Canada, as well as at Emory University and Georgia State University in the United States. He has also been a visiting researcher at Melbourne Business School and Monash University, and will be visiting the University of Bath in October 2025.

His primary area of research is financial econometrics, with a particular focus on financial risk modelling and simulation-based inference. His work has been published in leading journals such as the Journal of Econometrics and the Journal of Financial Econometrics.

This paper advances the econometric analysis of network connectedness by introducing exact simulation-based inference methods to assess pairwise and aggregated spill over effects among variables in vector autoregressive models. While the estimation of connectedness using forecast error variance decompositions is well-established, our contribution lies in the development of hypothesis testing procedures that provide a statistical foundation to formally test the significance of connectedness measures.

To address the multiple testing issue, we present detailed algorithms for both single-step and step-down p-value adjustments to effectively control the familywise error rate in finite samples. We also extend our methodology to include group-based analysis, thereby broadening the applicability of our approach. Simulation results confirm that our procedures not only ensure the simultaneous finite-sample correctness of the set of inferences but also demonstrate good statistical power.

We illustrate our inference procedures through empirical analyses of return and volatility spillovers among global stock markets, revealing new insights into financial market linkages and the vulnerability of financial networks to contagion.