摘要
本文运用最小生成树方法研究2006-2013年由全球56个股票市场指数组成的网络。研究发现,这些股票市场在网络中存在明显的地理聚集效应,而且标普500指数、香港恒生指数、荷兰AEX指数、法国CAC40指数、新加坡海峡时报指数、墨西哥IPC指数是网络中的关键节点;在金融危机中,网络的聚集效应在小范围内有所加强。本文还采用滑动窗口技术研究指数间平均系数和最短距离的均值,动态分析全球股票市场网络的稳定性。结果表明,监管者可以重点监测核心节点,以保证网络的整体稳定性。
This paper uses the minimum spanning tree method derived from physics, to study the data of 56 indices in the global stock market from 2006 to 2013, which is divided into three stages. The study find significant geographic aggregation effects in the network, especially the S&P 500 Index, the Hong Kong's Hang Seng Index, the Netherlands AEX index, the French CAC40 index, the Singapore's Straits Times Index, the Mexico IPC Index, are the key nodes in the network. While during the financial crisis, the aggregation effect has strengthened in a smaller area in the network. Then we use the sliding window technique to study the mean of average coefficient and the average shortest distance among the indices, dynamically analyze the stability of the global stock indices network. Through this analysis, regulators can focus on monitoring the core nodes to ensure the overall stability of the network.
出处
《南方金融》
北大核心
2014年第12期74-78,共5页
South China Finance
基金
国家自然科学基金重大研究计划重点项目<非常规突发事件应对决策任务规划的支持模型集成原理与方法研究>(项目编号:91024028)的资助
关键词
股票市场
股票指数
复杂网络
最小生成树
金融危机预警
Stock Market
Stock Index
Complex Network
Minimum Spanning Tree
Financial Crisis Warning
