2020
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Abstract: We investigate the dynamics of systemic risk of European companies using an approach that merges paradigmatic risk measures such as Marginal Expected Shortfall, CoVaR, and Delta CoVaR, with a Bayesian entropy estimation method. Our purpose is to bring to light potential spillover effects of the entropy indicator for the systemic risk measures computed on the 24 sectors that compose the STOXX 600 index. Our results show that several sectors have a high proclivity for generating spillovers. In general, the large… Show more

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Cited by 5 publications
(2 citation statements)
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References 57 publications
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“…The methodology for Bayesian entropy was previously described by Lupu et al [ 29 ], following the study by Archer, Park, and Pillow [ 30 ]. In the estimation process of the Bayesian entropy (denoted H ), we take into account that this is a deterministic function of a discrete distribution (π), which is influenced by parameter θ.…”
Section: Methodsmentioning
confidence: 99%
“…The connection between entropy and information enables the creation of structures that effectively capture the information contained in the modeling process, a feature that will be exploited in the stacking model as a new data structure D used to enhance prediction. Other studies that similarly exploit the concept of entropy in risk assessment are Gradojevic and Caric (2016); Lupu et al (2020) and Pichler and Schlotter (2020). It is a category representing the equivalence trap often observed in typical stacking models.…”
Section: 𝐻(𝑝 𝑝 … 𝑝 ) = − ∑ 𝑝 Log 𝑝mentioning
confidence: 99%