基于MF-DCCA模型的中国和美国股票市场的交叉相关性和多元分析
Yijun Chen1,2, Jun-Hao Zhang3, Lei Lu4
1College of Finance, Guizhou University of Commerce, Avenida 26, 550014, Guiyang, PR China.
Heliyon
|September 16, 2024
概括
中国 (CSI 300) 和美国 (S&P 500) 股票市场表现出多分体的动态,表明由投资者行为驱动的低效率,而不是纯粹的市场效率. 这些复杂的模式源于长期记忆和非线性效应.
科学领域:
- * 量化金融 量化金融
- * 金融市场分析
- * 复杂性科学 复杂性科学
背景情况:
- * 股票市场表现出复杂的动态,偏离传统的高效市场假设.
- *理解多元化对于评估市场行为,风险和可预测性至关重要.
- *以前的研究已经探讨了市场效率,但需要对主要全球市场进行详细的多分体比较.
研究的目的:
- * 为了比较中国 (CSI 300) 和美国 (S&P 500) 股票市场的多分体特征和影响因素.
- *分析这些市场的相关性,复杂性和不确定性.
- * 调查观察到的市场动态的潜在驱动因素.
主要方法:
- *从2018年3月到2023年3月对CSI 300和标准普尔500股票市场指数的分析.
- * 应用多分形确定交叉相关性分析 (MF-DCCA) 模型.
- *利用随机重组和阶段处理技术来隔离长期记忆和非线性效应.
主要成果:
- *CSI 300和标普500都表现出显著的多分位特征,在不同的时间尺度上具有不同的长期记忆,复杂性和不规则性.
- * 市场动向的特点是分形,受投资者的非理性和期望的影响,这表明市场不是完全有效的.
- * 确定了长期记忆和非线性效应作为观察到的多分体性质的主要贡献者.
结论:
- *这项研究提供了证据表明,中国和美国的股票市场都表现出多元化,挑战了完全市场效率的概念.
- * 投资者心理和期望在塑造市场动态方面发挥着重要作用,导致复杂的,碎形模式.
- *这些发现为投资者和监管机构提供了新的见解和分析方法,以更好地理解和导航市场的复杂性.
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