Tail Risk Connectedness Between US Industries

44 Pages Posted: 12 Jun 2018

See all articles by Linh Nguyen

Linh Nguyen

De Montfort University

Linh Xuan Diep Nguyen

University of Leicester

Linzhi Tan

Nottingham Trent University - Department of Accounting and Finance

Date Written: May 22, 2018

Abstract

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 takers, and tail-risk distributors among industries and confirm that the actual trade flow between industries is a major driver of their tail risk connectedness.

Keywords: Tail Risk Spillovers, Tail Risk Network, Business Linkage, Input-Output, Quantile Regression, LASSO

JEL Classification: C21, C51, C63, G10, G12, G18, G32, L14, L52

Suggested Citation

Nguyen, Linh and Nguyen, Linh Xuan Diep and Tan, Linzhi, Tail Risk Connectedness Between US Industries (May 22, 2018). Available at SSRN: https://ssrn.com/abstract=3183044 or http://dx.doi.org/10.2139/ssrn.3183044

Linh Nguyen (Contact Author)

De Montfort University ( email )

The Gateway
Leicester, LE1 9BH
United Kingdom

Linh Xuan Diep Nguyen

University of Leicester ( email )

University Road
Leicester, LE1 7RH
United Kingdom

Linzhi Tan

Nottingham Trent University - Department of Accounting and Finance ( email )

United Kingdom

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