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A tail dependence-based MST and their topological indicators in modelling systemic risk in the European insurance sector

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Document pages: 31 pages

Abstract: In the present work we analyse the dynamics of indirect connections betweeninsurance companies that result from market price channels. In our analysis weassume that the stock quotations of insurance companies reflect marketsentiments which constitute a very important systemic risk factor.Interlinkages between insurers and their dynamics have a direct impact onsystemic risk contagion in the insurance sector. We propose herein a new hybridapproach to the analysis of interlinkages dynamics based on combining thecopula-DCC-GARCH model and Minimum Spanning Trees (MST). Using thecopula-DCC-GARCH model we determine the tail dependence coefficients. Then, foreach analysed period we construct MST based on these coefficients. The dynamicsis analysed by means of time series of selected topological indicators of theMSTs in the years 2005-2019. Our empirical results show the usefulness of theproposed approach to the analysis of systemic risk in the insurance sector. Thetimes series obtained from the proposed hybrid approach reflect the phenomenaoccurring on the market. The analysed MST topological indicators can beconsidered as systemic risk predictors.

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