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Information network modeling for U.S. banking systemic risk

Giancarlo Nicola, Paola Cerchiello and Tomaso Aste

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: In this work we investigate whether information theory measures like mutual information and transfer entropy, extracted from a bank network, Granger cause financial stress indexes like LIBOR-OIS (London Interbank Offered Rate-Overnight Index Swap) spread, STLFSI (St. Louis Fed Financial Stress Index) and USD/CHF (USA Dollar/Swiss Franc) exchange rate. The information theory measures are extracted from a Gaussian Graphical Model constructed from daily stock time series of the top 74 listed US banks. The graphical model is calculated with a recently developed algorithm (LoGo) which provides very fast inference model that allows us to update the graphical model each market day. We therefore can generate daily time series of mutual information and transfer entropy for each bank of the network. The Granger causality between the bank related measures and the financial stress indexes is investigated with both standard Granger-causality and Partial Granger-causality conditioned on control measures representative of the general economy conditions.

Keywords: financial stress; granger causality; graphical models (search for similar items in EconPapers)
JEL-codes: F3 G3 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2020-11-23
New Economics Papers: this item is included in nep-ban, nep-cba, nep-fmk, nep-net, nep-ore and nep-rmg
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Citations: View citations in EconPapers (6) Track citations by RSS feed

Published in Entropy, 23, November, 2020, 22(11). ISSN: 1099-4300

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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:107563

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