Estimating Global Bank Network Connectedness
Francis Diebold (),
Laura Liu () and
Kamil Yilmaz ()
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Mert Demirer: MIT
Koç University-TUSIAD Economic Research Forum Working Papers from Koc University-TUSIAD Economic Research Forum
We use lasso methods to shrink, select and estimate the network linking the publicly-traded subset of the world's top 150 banks, 2003-2014. We characterize static network connectedness using full-sample estimation and dynamic network connectedness using rolling-window estimation. Statistically, we find that global banking connectedness is clearly linked to bank location, not bank assets. Dynamically, we find that global banking connectedness displays both secular and cyclical variation. The secular variation corresponds to gradual increases/decreases during episodes of gradual increases/decreases in global market integration. The cyclical variation corresponds to sharp increases during crises, involving mostly cross-country, as opposed to within-country, bank linkages.
Keywords: Systemic risk; connectedness; systemically important financial institutions; vector autoregression; variance decomposition; lasso; elastic net; adaptive lasso; adaptive elastic net. (search for similar items in EconPapers)
JEL-codes: C32 G21 (search for similar items in EconPapers)
Pages: 36 pages
New Economics Papers: this item is included in nep-ban and nep-net
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Journal Article: Estimating global bank network connectedness (2018)
Working Paper: Estimating Global Bank Network Connectedness (2017)
Working Paper: Estimating Global Bank Network Connectedness (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:koc:wpaper:1512
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