Dynamic Bivariate Peak Over Threshold Model for Joint Tail Risk Dynamics of Financial Markets
Dynamic Bivariate Peak Over Threshold Model for Joint Tail Risk Dynamics of Financial Markets
复制标题
金融市场联合尾部风险动态的动态双变量阈值峰值模型
DOI：
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发表时间：
2020
影响因子：
3
通讯作者：
Zifeng Zhao
中科院分区：
文献类型：
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作者：
Zifeng Zhao
摘要提出了一种新的动态双变量峰值超阈值(POT)模型来研究金融市场联合尾部风险的时变行为。该框架提供了边际和联合尾部风险动态的同时建模，并将现有的尾部风险文献从单变量维度推广到多变量维度。我们引入了一个自然且可解释的尾部连通性度量，并检验了全球股票市场的联合尾部行为的动态：经验证据表明，来自同一大洲的市场具有时变的高水平的联合尾部风险，并且尾部连通性在危机期间增加。我们进一步丰富了尾部风险文献，发展了一种新的基于双变量联合尾部风险最小化的投资组合优化方法，在回溯测试中给出了有希望的风险回报性能。
Abstract We propose a novel dynamic bivariate peak over threshold (PoT) model to study the time-varying behavior of joint tail risk in financial markets. The proposed framework provides simultaneous modeling for dynamics of marginal and joint tail risk, and generalizes the existing tail risk literature from univariate dimension to multivariate dimension. We introduce a natural and interpretable tail connectedness measure and examine the dynamics of joint tail behavior of global stock markets: empirical evidence suggests markets from the same continent have time-varying and high-level joint tail risk, and tail connectedness increases during periods of crisis. We further enrich the tail risk literature by developing a novel portfolio optimization procedure based on bivariate joint tail risk minimization, which gives promising risk-rewarding performance in backtesting.