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作 者:关伟[1] 刘丽萍 邵梯航 Guan Wei;Liu Liping;Shao Tihang
出 处:《南开学报(哲学社会科学版)》2023年第1期61-73,共13页Nankai Journal:Philosophy,Literature and Social Science Edition
基 金:国家自然科学基金青年项目(71703111)。
摘 要:为有效识别影响中国股市波动的外部风险因子,我们以上证综指和深证成指为研究对象,采用美国经济不确定性指数、金融不确定性指数、经济政策不确定性指数以及地缘风险指数度量美国的不确定性冲击,并通过单因子和双因子的混频波动率GARCH-MIDAS模型考察美国四类不确定性冲击对中国股市波动的影响以及不同市场的异质性反应,进而识别中国股市波动的外部风险因子。研究结果发现:(1)相比于其他三类不确定性冲击,美国金融不确定性对中国股市波动具有显著的正向影响;(2)美国金融不确定性对上证综指和深证成指波动的影响存在异质性,对深证成指影响程度更大;(3)基于已实现波动率与金融不确定性的双因子模型可以改进单因子模型的估计和预测效果,且MCS检验结果进一步表明,对于上证综指和深证成指,包含金融不确定性的模型始终具有稳定的样本外预测优势。因此,美国金融不确定性是中国股市波动的一个重要影响因子,纳入美国金融不确定性对提高中国股市波动的预测精度具有积极作用,有利于预测和控制股市波动,促进金融市场的平稳运行。In order to effectively identify the external risk factors affecting the volatility of China’s stock market,this paper takes the Shanghai Composite Index and the Shenzhen Component Index as the research objects and constructs a U.S. Economic Uncertainty Index, Financial Uncertainty Index, Economic Policy Uncertainty Index and geopolitical risk index respectively. Then this paper uses the single-factor and double-factor of mixed frequency GARCHMIDAS models to examine the impact of four types of U.S. uncertainty shocks on China’s stock market volatility and the differences in different stock markets, and further identifies the external risk factors of China’s stock market volatility. The study found that: 1) compared with other uncertainties, the U.S. financial uncertainty has a significant positive impact on the volatility of China’s stock market;2) U.S. financial uncertainty has a significant heterogeneous impact on the Shanghai Composite Index and Shenzhen Component Index, with a greater impact on the Shenzhen Component Index;and 3) the double-factor model based on realized volatility and financial uncertainty can improve the estimation and forecasting effect of the single-factor model, and the MCS test results further demonstrates that the model including financial uncertainty FU always has a stable out-of-sample forecasting advantage. Therefore, the U.S. financial uncertainty is an important source of China’s stock market volatility. The inclusion of FU in the benchmark GARCH-MIDAS model has a positive effect on improving the forecasting accuracy of stock market volatility, which is beneficial to predict the volatility of China’s stock market and promote the smooth operation of the macro economy and financial market.
关 键 词:美国不确定性 中国股市波动 GARCH-MIDAS模型 影响因子
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