A Bayesian Entropy Approach to Sectoral Systemic Risk Modeling

Radu Lupu; Adrian Cantemir Călin; Cristina Georgiana Zeldea; Iulia Lupu

doi:10.3390/e22121371

A Bayesian Entropy Approach to Sectoral Systemic Risk Modeling

Entropy (Basel). 2020 Dec 4;22(12):1371. doi: 10.3390/e22121371.

Authors

Radu Lupu^{1

2}, Adrian Cantemir Călin^{1

2}, Cristina Georgiana Zeldea^{1

3}, Iulia Lupu⁴

Affiliations

¹ Department of International Business and Economics, Bucharest University of Economic Studies, 010404 Bucharest, Romania.
² Institute for Economic Forecasting, Romanian Academy, 050711 Bucharest, Romania.
³ Institute for World Economy, Romanian Academy, 050711 Bucharest, Romania.
⁴ "Victor Slăvescu" Centre for Financial and Monetary Research, Romanian Academy, 050711 Bucharest, Romania.

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 largest influences are delivered by Capital Goods, Banks, Diversified Financials, Insurance, and Real Estate. We also bring detailed evidence on the sectors that are the most pregnable to spillovers and on those that represent the main contributors of spillovers.

Keywords: Bayesian inference; economic sectors; entropy measures; spillovers; systemic risk measurement.