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A network-based method for detecting critical events of correlation dynamics in financial markets
EPL ( IF 1.8 ) Pub Date : 2020-09-17 , DOI: 10.1209/0295-5075/131/50001
Chun-Xiao Nie

In recent years, the dynamics of the financial correlation matrix has been widely studied. This study applies the Frobenius distance-based kNN ( k nearest neighbour) network to analyse the time-varying characteristics of the correlation matrix, especially during the period of drastic change. We use the influence-strength ( IS ) index to detect when the correlation matrix structure changes dramatically. Based on the data from the US stock market, we tested the effectiveness of the method. The IS -based method accurately detects some important events from the 2008 crisis to the 2020 crisis. Our calculations indicate that IS -based analysis provides an effective tool for analysing financial correlation dynamics.

中文翻译:

基于网络的金融市场相关动态关键事件检测方法

近年来,人们广泛研究了财务相关矩阵的动力学。这项研究应用基于Frobenius距离的kNN(k最近邻)网络来分析相关矩阵的时变特征,尤其是在急剧变化的时期。我们使用影响强度(IS)指数来检测相关矩阵结构何时发生显着变化。根据美国股市的数据,我们测试了该方法的有效性。基于IS的方法可以准确地检测出从2008年危机到2020年危机的一些重要事件。我们的计算表明,基于IS的分析为分析财务相关动态提供了有效的工具。
更新日期:2020-09-20
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