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首页> 外文期刊>International Journal of Electronic Commerce >How Do the Global Stock Markets Influence One Another? Evidence from Finance Big Data and Granger Causality Directed Network
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How Do the Global Stock Markets Influence One Another? Evidence from Finance Big Data and Granger Causality Directed Network

机译：全球股市如何彼此影响？ 来自金融大数据和格兰杰因果关系的证据

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摘要

The recent financial network analysis approach reveals that the topologies of financial markets have an important influence on market dynamics. However, the majority of existing Finance Big Data networks are built as undirected networks without information on the influence directions among prices. Rather than understanding the correlations, this research applies the Granger causality test to build the Granger Causality Directed Network for 33 global major stock market indices. The paper further analyzes how the markets influence one another by investigating the directed edges in the different filtered networks. The network topology that evolves in different market periods is analyzed via a sliding window approach and Finance Big Data visualization. By quantifying the influences of market indices, 33 global major stock markets from the Granger causality network are ranked in comparison with the result based on PageRank centrality algorithm. Results reveal that the ranking lists are similar in both approaches where the U.S. indices dominate the top position followed by other American, European, and Asian indices. The lead-lag analysis reveals that there is lag effects among the global indices. The result sheds new insights on the influences among global stock markets with implications for trading strategy design, global portfolio management, risk management, and markets regulation.
机译：最近的财务网络分析方法揭示了金融市场的拓扑对市场动态有重要影响。然而，大多数现有的金融大数据网络都被建立为无向网络，而无需对价格之间的影响方向的信息。本研究而不是了解相关性，而不是了解格兰杰因果关系测试，为33个全球主要股票市场指数构建格兰杰因果关系。本文进一步分析了市场如何通过调查不同过滤网络中的定向边缘来彼此影响。通过滑动窗口方法分析不同市场时期在不同的市场时期演变的网络拓扑，并为大数据可视化进行了资金。通过量化市场指标的影响，与基于PageRank中心算法的结果相比，来自格兰杰因果关系网络的33个全球主要股市。结果表明，排名列表在美国指数主导着最重要的位置，然后是其他美国，欧洲和亚洲指数的方法相似。引导滞后分析表明，全球索引之间存在滞后效应。结果揭示了对全球股市影响的新见解，对交易策略设计，全球组合管理，风险管理和市场监管的影响影响。

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