Cluster formation and evolution in networks of financial market indices

IF 0.3 Q4 BUSINESS, FINANCE
Leonidas Sandoval Junior
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引用次数: 36

Abstract

Using data from world stock exchange indices prior to and during periods of global financial crises, clusters and networks of indices are built for different thresholds and diverse periods of time, so that it is then possible to analyze how clusters are formed according to correlations among indices and how they evolve in time, particularly during times of financial crises. Further analysis is made on the eigenvectors corresponding to the second highest eigenvalues of the correlation matrices, revealing a structure peculiar to markets that operate in different time zones.
金融市场指数网络中的集群形成与演化
利用全球金融危机之前和期间的世界证券交易所指数的数据,针对不同的阈值和不同的时间段构建指数集群和指数网络,这样就有可能根据指数之间的相关性分析集群是如何形成的,以及它们如何随时间演变,特别是在金融危机期间。对相关矩阵第二高特征值对应的特征向量进行了进一步分析,揭示了不同时区市场特有的结构。
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来源期刊
Algorithmic Finance
Algorithmic Finance BUSINESS, FINANCE-
CiteScore
0.40
自引率
0.00%
发文量
6
期刊介绍: Algorithmic Finance is both a nascent field of study and a new high-quality academic research journal that seeks to bridge computer science and finance. It covers such applications as: High frequency and algorithmic trading Statistical arbitrage strategies Momentum and other algorithmic portfolio management Machine learning and computational financial intelligence Agent-based finance Complexity and market efficiency Algorithmic analysis of derivatives valuation Behavioral finance and investor heuristics and algorithms Applications of quantum computation to finance News analytics and automated textual analysis.
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