Abstract
Social trading platforms (STPs) are transparent online markets governed by a scopic regime, where order flow is publicly disclosed and participants are subject to constant reciprocal scrutiny. Participants on STPs can be categorized into trade leaders and copiers, where the former execute unique trades and manage the funds allocated to them by the latter in return for compensation. Given limited individual capacity and the competition to attract copiers, we investigate whether the scopic regime produces excess and perpetual conformism among trade leaders. Using data from a popular STP, and from an anonymous traditional foreign exchange broker, we show that the scopic regime produces excess levels of herding. Under the scopic environment, we find that herding is high when market information is scarce, which is evidence of herding due to informational cascades. We find herding to be relatively low among risk-seeking trade leaders, which may be a sign of overconfidence. Herding is high for larger trades, suggesting that traders herd to avoid the disappointment associated with underperforming on large positions. Finally, we show that herding in the scopic environment persists at much higher levels compared to traditional environments. Our findings indicate that exposure to a scopic information-rich environment augments the limitations and personal biases of individual traders, thus producing excess and perpetual herding.
Original language | English |
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Pages (from-to) | 1144-1175 |
Number of pages | 32 |
Journal | European Journal of Finance |
Volume | 24 |
Issue number | 14 |
Early online date | 4 Dec 2017 |
DOIs | |
Publication status | Published - 22 Sept 2018 |
Externally published | Yes |
Bibliographical note
We are very grateful to Ian Marsh, Ingmar Nolte, and two anonymous reviewers for their invaluable feedback. We thank the seminar participants at the London School of Economics and Political Science and Copenhagen Business School, as well as the conference audiences at Queen Mary University of London and the Academy of Behavioral Finance & Economics for their constructive comments and suggestions. Special thanks are extended to the two anonymous trading platforms for providing the data sets, which made this research possible.Publisher Copyright:
© 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group.
Keywords
- general
- information and market efficiency
- informational finance markets