2021
DOI: 10.1007/s10693-021-00366-9
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Exploring the Systemic Risk of Domestic Banks with ΔCoVaR and Elastic-Net

Abstract: We analyze the systemic risk of Italian banks with the ΔCoVaR from a bivariate normal GARCH model. The results show that it is a good measure of systemic risk and is applicable to the ranking of Italian other systemically important institutions. Using an elastic-net approach, we identify the balance sheet and market variables that explain the ΔCoVaR of Italian banks. The analysis confirms that these variables are key determinants of systemic importance and highlights how higher capitalization is beneficial to … Show more

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Cited by 3 publications
(2 citation statements)
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“…For example, Brogi et al (2021) compare the G-SII buffer rankings to systemic risk rankings based on Huang et al (2012) and find significant differences in the two approaches and argue that the regulatory framework would benefit by incorporating also a risk contribution metric into generating systemic rankings. Bianchi and Sorrentino (2021), on the other hand, explore a small sample consisting of the four Italian banks designated as systemically important and largely find consistency in the ranking based on the CoVaR measure and based on the O-SII buffer rates set by the Italian central bank. Yet, having higher frequency data allows them to link systemic risk estimates to the evolution of bank characteristics and conditions.…”
Section: Related Literaturementioning
confidence: 91%
“…For example, Brogi et al (2021) compare the G-SII buffer rankings to systemic risk rankings based on Huang et al (2012) and find significant differences in the two approaches and argue that the regulatory framework would benefit by incorporating also a risk contribution metric into generating systemic rankings. Bianchi and Sorrentino (2021), on the other hand, explore a small sample consisting of the four Italian banks designated as systemically important and largely find consistency in the ranking based on the CoVaR measure and based on the O-SII buffer rates set by the Italian central bank. Yet, having higher frequency data allows them to link systemic risk estimates to the evolution of bank characteristics and conditions.…”
Section: Related Literaturementioning
confidence: 91%
“…Regarding the factors driving banks' systemic behavior, literature identifies many variables. From the balance sheet perspective, size is an important predictor that amplifies systemic distress (Laeven et al, 2016;Bostandzic and Weiß, 2018;Varotto and Zhao, 2018), together with the lower quality of their loan portfolios (Bostandzic and Weiß, 2018;Andrieș and Sprincean, 2021), whereas better capitalization dampens it (Laeven et al, 2016;Bianchi et al, 2022;Andrieș et al, 2022). Diversification through non-traditional sources of income can go either way (Sedunov, 2016;Brunnermeier et al, 2020;Andrieș and Sprincean, 2021;Karolyi et al, 2022).…”
Section: Literature Reviewmentioning
confidence: 99%