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将独立成分分析(ICA)方法引入金融衍生品市场与基础市场之间的波动溢出研究,克服了传统方法解决高维金融时间序列波动问题时的障碍。通过与VECH、BEKK和DCC等传统多元GARCH模型的对比分析,本文所建立的ICA-EGARCH-M模型在解决高维问题时体现出一定的优势。在实证研究中,应用该模型考察了美国、英国、日本和中国香港的股指期货市场及其股票市场对我国股票市场的共同波动溢出。结果表明ICA-EGARCH-M模型不仅验证了波动溢出效应的存在,而且反映出了波动溢出的主要来源,能够较好地解决高维金融时间序列数据的波动溢出问题。
The introduction of Independent Component Analysis (ICA) into the volatility spillover between the financial derivatives market and the basic market overcomes the obstacles of traditional methods to solve the volatility problems of high-dimensional financial time series. Compared with traditional multivariate GARCH models such as VECH, BEKK and DCC, the ICA-EGARCH-M model established in this paper shows some advantages in solving high-dimensional problems. In the empirical study, this model is used to examine the volatility of the stock index futures market and its stock market in China, the United States, the United Kingdom, Japan and Hong Kong, China. The results show that the ICA-EGARCH-M model not only verifies the existence of volatility spillover, but also reflects the main source of volatility spillover, which can well solve the volatility spillover problem of high-dimensional financial time series data.