1. bookVolume 9 (2020): Issue 2 (May 2020)
Journal Details
License
Format
Journal
eISSN
2336-9205
First Published
11 Mar 2014
Publication timeframe
3 times per year
Languages
English
access type Open Access

Econophysical bourse volatility – Global Evidence

Published Online: 02 Jun 2020
Volume & Issue: Volume 9 (2020) - Issue 2 (May 2020)
Page range: 87 - 107
Received: 04 Dec 2018
Accepted: 14 Aug 2019
Journal Details
License
Format
Journal
eISSN
2336-9205
First Published
11 Mar 2014
Publication timeframe
3 times per year
Languages
English
Abstract

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.

Keywords

JEL Classification

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