We use the Least Absolute Shrinkage and Selection Operator (LASSO) quantile regression technique to construct and analyse the complete tail risk connectedness network of the whole US industry system. We also investigate the empirical relationship between input–output linkages and the tail risk spillovers among US industries. Our findings identify the tail‐risk drivers, tail‐risk receivers, and tail‐risk distributors among industries and confirm that the actual trade flow between industries is a major driver of their tail risk connectedness
Purpose: This study aims to examine the tail connectedness between the Chinese and Association of So...
We propose a semiparametric measure to estimate systemic interconnectedness across financial institu...
CoVaR is a measure for systemic risk of the networked financial system conditional on institutions b...
We use the Least Absolute Shrinkage and Selection Operator (LASSO) quantile regression technique to ...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
© 2020 Elsevier B.V. We construct the complete network of tail risk spillovers among major cryptocur...
This paper contributes to model the industry interconnecting structure in a network context. General...
Learning how the financial risk has been transmitted between industries in China before and after so...
This study investigates the tail risk spillovers between the crude oil market and the stock markets ...
We develop a new technique to estimate vector autoregressions with a common factor error structure b...
CoVaR is a measure for systemic risk of the networked financial system conditional on institutions b...
In this paper, we propose a novel approach to examine the risk spillovers between FinTech firms and ...
This study examines potential tail spillovers between insurance tokens and conventional stocks using...
We report on time-varying network connectedness within three banking systems: North America (NA), th...
New contagion measures based on theories of copula, heavy-tailed distributions and networks are intr...
Purpose: This study aims to examine the tail connectedness between the Chinese and Association of So...
We propose a semiparametric measure to estimate systemic interconnectedness across financial institu...
CoVaR is a measure for systemic risk of the networked financial system conditional on institutions b...
We use the Least Absolute Shrinkage and Selection Operator (LASSO) quantile regression technique to ...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
© 2020 Elsevier B.V. We construct the complete network of tail risk spillovers among major cryptocur...
This paper contributes to model the industry interconnecting structure in a network context. General...
Learning how the financial risk has been transmitted between industries in China before and after so...
This study investigates the tail risk spillovers between the crude oil market and the stock markets ...
We develop a new technique to estimate vector autoregressions with a common factor error structure b...
CoVaR is a measure for systemic risk of the networked financial system conditional on institutions b...
In this paper, we propose a novel approach to examine the risk spillovers between FinTech firms and ...
This study examines potential tail spillovers between insurance tokens and conventional stocks using...
We report on time-varying network connectedness within three banking systems: North America (NA), th...
New contagion measures based on theories of copula, heavy-tailed distributions and networks are intr...
Purpose: This study aims to examine the tail connectedness between the Chinese and Association of So...
We propose a semiparametric measure to estimate systemic interconnectedness across financial institu...
CoVaR is a measure for systemic risk of the networked financial system conditional on institutions b...