Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/35915
Appears in Collections:Accounting and Finance Journal Articles
Peer Review Status: Refereed
Title: Numerological Superstitions and Market-Wide Herding: Evidence from China
Author(s): Cui, Yueting
Gavriilidis, Konstantinos
Gabka, Bartosz
Kallinterakis, Vasileios
Contact Email: konstantinos.gavriilidis@stir.ac.uk
Keywords: Superstition
Herding
Noise
Retail investors
China
Issue Date: May-2024
Date Deposited: 19-Mar-2024
Citation: Cui Y, Gavriilidis K, Gabka B & Kallinterakis V (2024) Numerological Superstitions and Market-Wide Herding: Evidence from China. <i>International Review of Financial Analysis</i>, 93. https://doi.org/10.1016/j.irfa.2024.103199
Abstract: We empirically investigate the effect of traditional Chinese numerological superstitions over market-wide herding in the Shanghai and Shenzhen stock exchanges for the 2000–2020 period, based on a classification of stocks as lucky/unlucky contingent on the presence of digits deemed numerologically lucky/unlucky in their tickers. We find no compelling evidence that herding is more pronounced in those superstitious stocks, as compared to the rest of the stock market. Both superstitious stock-types herd exclusively on high-volatility days and exhibit some pronounced patterns in up vs down markets; these effects are not significantly different from the behaviour of non-superstitious stocks, however. Similarly, herding in both superstitious stock-types is largely noise-driven, but the same effect is observed for non-superstitious stocks. The similarities in herding between superstitious and non-superstitious stocks suggest that numerological superstitions do not motivate significantly stronger herding in Chinese markets.
DOI Link: 10.1016/j.irfa.2024.103199
Rights: This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You are not required to obtain permission to reuse this article. To request permission for a type of use not listed, please contact Elsevier Global Rights Department.
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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