Intraday herding on a cross-border exchange

Panagiotis Andrikopoulos, Vasileios Kallinterakis, Mario Pedro Leite Ferreira and Thanos Verousis (thanos.verousis@vlerick.com)

International Review of Financial Analysis, 2017, vol. 53, issue C, 25-36

Abstract: This study investigates intraday herding on the Euronext, the world's first cross-border consolidated exchange. Intraday herding is significant in the Euronext as a group and presents us with size, industry and country effects. Importantly, the trading dynamics of the group's member markets significantly affect each other and can, in the case of the Netherlands, promote herding formation. Intraday herding is found to be significant before, during and after the 2007–09 financial crisis period, with its presence appearing the least strong during the crisis. Overall, we demonstrate for the first time in the literature that cross-border exchanges harbour versatile herding dynamics at intraday level, a finding which reflects recent advances in financial technology and the ongoing financial integration in Europe.

Keywords: Tick data; Intraday herding; Cross-border groups; Euronext (search for similar items in EconPapers)
JEL-codes: G02 G15 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1057521917301023
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:53:y:2017:i:c:p:25-36

DOI: 10.1016/j.irfa.2017.08.010

Access Statistics for this article

International Review of Financial Analysis is currently edited by B.M. Lucey

More articles in International Review of Financial Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu (repec@elsevier.com).