论文标题
基于尾巴依赖的MST及其在欧洲保险部门建模系统风险时的拓扑指标
A tail dependence-based MST and their topological indicators in modelling systemic risk in the European insurance sector
论文作者
论文摘要
在目前的工作中，我们分析了由市场价格渠道导致的保险公司之间间接联系的动态。在我们的分析中，我们假设保险公司的股票报价反映了构成非常重要的系统性风险因素的市场情绪。保险公司与其动态之间的联系直接影响保险部门的系统性风险传染。我们在此提出了一种新的混合方法，以组合Copula-DCC-Garch模型和最小跨越树（MST）的分析动态分析。使用Copula-DCC-Garch模型，我们确定尾部依赖系数。然后，在每个分析期间，我们都基于这些系数构建MST。在2005 - 2019年间，通过选定的MST拓扑指标的时间序列分析了该动力学。我们的经验结果表明，拟议方法在保险部门对系统风险分析的有用性。从拟议的混合方法获得的时代序列反映了市场上发生的现象。分析的MST拓扑指标可以视为系统性风险预测因子。
In the present work we analyse 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. We propose herein 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 analysed period we construct MST based on these coefficients. The dynamics is analysed by means of time series of selected topological indicators of the MSTs in the years 2005-2019. Our empirical results show the usefulness of the proposed approach to the analysis of systemic risk in the insurance sector. The times series obtained from the proposed hybrid approach reflect the phenomena occurring on the market. The analysed MST topological indicators can be considered as systemic risk predictors.
