This paper employs a new framework, the high-dimensional conditional Value-at-Risk
(CoVaR) connectedness based on the LASSO-VAR model, to explore the conditional …

Network modeling of high-dimensional time series data is a key learning task due to its
widespread use in a number of application areas, including macroeconomics, finance, and …

In this paper, we gauge the degree of interconnectedness and quantify the linkages
between global and other systemically important institutions, and the global financial system …

The aim of this paper is to propose a new network measure of systemic risk contributions
that combines the pair-wise Granger causality approach with the leave-one-out concept …

The recent global financial crisis has triggered a huge interest in the use of network
concepts and network tools to better understand how instabilities can propagate through the …

This paper presents a novel approach to investigate and model the network of euro area
banks' large exposures within the global banking system. Drawing on a unique dataset, the …

We develop an LM test for Granger causality in high-dimensional (HD) vector autoregressive
(VAR) models based on penalized least squares estimations. To obtain a test retaining the …

This study examines the interconnection structure of Islamic and conventional banks and
how they transmit extreme risks to each other. This appears to be a particular problem …

Purpose The current study aims to analyze the linkage among bank competition, liquidity
and loan price in an interconnected bank network system. Design/methodology/approach …

We provide a new metric for the systemic importance of banks based on the intensity of
spillovers of daily CDS movements. We denote this a bank's Individual Systemic Risk (ISR) …