Statistical Modelling of Downside Risk Spillovers

Daniel Felix Ahelegbey

No 193, DEM Working Papers Series from University of Pavia, Department of Economics and Management

Abstract: We extend the extreme downside hedge methodology to model sensitivity interconnectedness of market returns to the tail risk of other markets under turbulent conditions. We derive the interconnectedness via Bayesian graph structural learning. The empirical application examines the dynamic interconnectedness among 15 major markets, including G10 economies, during turbulent times. We investigate whether downside risk connections among these major markets are merely anecdotal or provide evidence of contagion and the most central market for spillover propagation. The result shows that the Covid-19 induced downside risk connections record the highest density, suggesting stronger evidence of contagion in the coronavirus pandemic than during the financial and eurozone crisis. Central to the spillover propagation is the finding that most of the transmitters and recipients of downside risk are EU markets.

Keywords: Bayesian Inference; Centrality; Contagion; Conditional VaR; Downside Risk; Extreme downside hedge; Financial Crises; Financial Networks. (search for similar items in EconPapers)
JEL-codes: C31 C58 G01 G12 (search for similar items in EconPapers)
Pages: 13
Date: 2020-10
New Economics Papers: this item is included in nep-net and nep-rmg
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http://dem-web.unipv.it/web/docs/dipeco/quad/ps/RePEc/pav/demwpp/DEMWP0193.pdf (application/pdf)

Related works:
Journal Article: Statistical Modelling of Downside Risk Spillovers (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:pav:demwpp:demwp0193

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