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以Divisive方法诊断国际石油和中国股票二元时序突变性后,为克服Copula等方法在描述金融市场局部相关性的不足,利用局部正态相关系数(Local Gussian Correlation)研究突变结构下国际油价对中国股市整体及不同行业股票的冲击影响。实证结果表明:局部正态相关系数模型能充分刻画石油与股票价格之间的局部相关特征。在突变点显著存在的基础上,LGC捕捉到两市的相关结构经历了从不相关、正相关到显著正相关的变化趋势。石油价格下跌对中国股市的影响更大。和西方成熟市场不同,国际石油对中国股市表现为正向冲击关系,在重大事件影响下两市的共生风险会显著累积集聚,选择它们进行投资组合风险分散性较差。
After using Divisive method to diagnose the mutation of binary sequence of international oil and Chinese stocks, in order to overcome the shortcomings of Copula and other methods in describing the local correlation of financial markets, the local normalized correlation coefficient (Local Gussian Correlation) Impact of the stock market as a whole and the impact of different sectors of the stock. The empirical results show that the local normal correlation coefficient model can fully characterize the local correlation between oil and stock prices. Based on the significant existence of mutation points, LGC captures the trend of irrelevance, positive correlation and significant positive correlation between the relevant structures of the two cities. The drop in oil prices has a greater impact on the Chinese stock market. Unlike the mature markets in the West, international oil has a positive impact on the Chinese stock market. Under the influence of major events, the symbiotic risks of the two cities will accumulate significantly. Choosing them for portfolio risk dispersion is poor.