We construct time-varying tail risk networks to investigate systemic risk spillovers in the Belt
and Road (B&R) stock markets during 2008–2021. Network metrics clearly reflect aggregate …

In this paper, we introduce quantile coherency to measure general dependence structures
emerging in the joint distribution in the frequency domain and argue that this type of …

We propose a new systemic risk index based on the interdependence of extreme downside
movements of stock returns using the cross-quantilogram and network analysis approach …

This article examines the return and volatility spillover effects among the S&P 500, crude oil,
and gold by employing the spillover index of Diebold and Yilmaz (2012). Monthly realized …

We assess the degree of connectedness among 16 metals that are critical for the production
of clean energy technologies. These commodities are the constituents of the Energy …

The interdependence, dynamics and riskiness of financial institutions are the key features
frequently tackled in financial econometrics. We propose a Tail Event driven Network …

Individuals or companies in a large social or financial network often display rather
heterogeneous behaviors for various reasons. In this work, we propose a network vector …

LASSO-driven inference in time and space Page 1 The Annals of Statistics 2021, Vol. 49, No.
3, 1702–1735 https://doi.org/10.1214/20-AOS2019 © Institute of Mathematical Statistics …

Text of abstract In the big data era, it is common to encounter data observed at different
frequencies. This raises the problem of how to explore the heterogeneous nonlinear …

This paper constructs a tail event driven network to investigate the interdependence of tail
risks among industries in the Chinese stock market from 2014 to 2019, and identifies …