Abstract
In the present work, we analyze the dynamics of indirect connections between insurance companies that result from market price channels. In our analysis, we assume that the stock quotations of insurance companies reflect market sentiments, which constitute a very important systemic risk factor. Interlinkages between insurers and their dynamics have a direct impact on systemic risk contagion in the insurance sector. Herein, we propose a new hybrid approach to the analysis of interlinkages dynamics based on combining the copula-DCC-GARCH model and minimum spanning trees (MST). Using the copula-DCC-GARCH model, we determine the tail dependence coefficients. Then, for each analyzed period we construct MST based on these coefficients. The dynamics are analyzed by means of the time series of selected topological indicators of the MSTs in the years 2005–2019. The contribution to systemic risk of each institution is determined by analyzing the deltaCoVaR time series using the copula-DCC-GARCH model. Our empirical results show the usefulness of the proposed approach to the analysis of systemic risk (SR) in the insurance sector. The times series obtained from the proposed hybrid approach reflect the phenomena occurring in the market. We check whether the analyzed MST topological indicators can be considered as systemic risk predictors.
Highlights
Despite many studies that use different methodological and empirical approaches to identify and analyze systemic risk (SR) in the insurance sector, there is still no consistent theory to monitor it effectively
We focus on the structure of interlinkages between insurance companies, which plays a key role in the spread of systemic risk in this sector
We carry out the analysis of the dynamics of interconnections between insurance companies using a new hybrid approach based on the combination of the copula-DCC-GARCH model and minimum spanning trees (MST)
Summary
Despite many studies that use different methodological and empirical approaches to identify and analyze systemic risk (SR) in the insurance sector, there is still no consistent theory to monitor it effectively. We assume that stock market quotations of insurance companies reflect market sentiment, which is a very important systemic risk factor. We propose a new hybrid approach to analyzing the dynamics of interconnections, based on combining the copula-DCC-GARCH and minimum spanning trees (MST). Using the copula-DCC-GARCH model, we determine tail dependence coefficients Based on these coefficients for each analyzed period, we determine the “distance” matrix between insurance companies using the Mantegna metric (Mantegna and Stanley 1999) and construct minimum spanning trees. To check whether the time series of topological indicators of the network of connections between insurance companies obtained using the proposed hybrid approach reflect the situation on the financial market and whether they can be used as predictors of systemic risk in the insurance sector.
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