文章基本信息

标题：Econophysical bourse volatility – Global Evidence
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作者：Bikramaditya Ghosh ; Krishna MC
期刊名称：Journal of Central Banking Theory and Practice
电子版ISSN：2336-9205
出版年度：2020
卷号：9
期号：2
页码：87-107
DOI：10.2478/jcbtp-2020-0015
语种：English
出版社：Sciendo
摘要：Financial Reynolds number (Re) has been proven to have the capacity to predict volatility, herd behaviour and nascent bubble in any stock market (bourse) across the geographical boundaries. This study examines forty two bourses (representing same number of countries) for the evidence of the same. This study finds specific clusters of stock markets based on embedded volatility, herd behaviour and nascent bubble. Overall the volatility distribution has been found to be Gaussian in nature. Information asymmetry hinted towards a well-discussed parameter of ‘financial literacy’ as well. More than eighty percent of indices under consideration showed traces of mild herd as well as bubble. The same indices were all found to be predictable, despite being stochastic time series. In the end, financial Reynolds number (Re) has been proved to be universal in nature, as far as volatility, herd behaviour and nascent bubble are concerned.
关键词：Financial Reynolds number;volatility;Herding;Bubble;Econophysics