Tail risk connectedness between US industries

Nguyen, LH, Nguyen, LXD and Tan, L ORCID: https://orcid.org/0000-0001-6986-1923, 2020. Tail risk connectedness between US industries. International Journal of Finance and Economics. ISSN 1076-9307

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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 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.

Item Type:	Journal article
Publication Title:	International Journal of Finance and Economics
Creators:	Nguyen, L.H., Nguyen, L.X.D. and Tan, L.
Publisher:	Wiley
Date:	15 July 2020
ISSN:	1076-9307
Identifiers:	Number Type 10.1002/ijfe.1979 DOI 1344582 Other
Rights:	This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Divisions:	Schools > Nottingham Business School
Record created by:	Jonathan Gallacher
Date Added:	06 Aug 2020 09:58
Last Modified:	31 May 2021 15:18
URI:	https://irep.ntu.ac.uk/id/eprint/40352

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