Herding Unmasked: Insights into Cryptocurrencies, Stocks and US ETFs
An Pham Ngoc Nguyen, Martin Crane, Thomas Conlon, Marija Bezbradica

TL;DR
This study investigates herding behavior across stocks, US ETFs, and cryptocurrencies using recent data, revealing subset-level herding linked to specific events and contagion effects, with US ETFs playing a central role.
Contribution
First comprehensive analysis of herding across three investment types and at community levels, employing graph-based techniques to uncover subset-specific herding patterns.
Findings
Herding patterns are similar for stocks and US ETFs.
Herding exists at subset level, often triggered by specific events.
US ETFs propagate herding and act as trend drivers.
Abstract
Herding behavior has become a familiar phenomenon to investors, with potential dangers of both undervaluing and overvaluing assets, while also threatening market stability. This study contributes to the literature on herding behavior by using a recent dataset, covering the most impactful events of recent years. To our knowledge, this is the first study examining herding behavior across three different types of investment vehicle and also the first study observing herding at a community (subset) level. Specifically, we first explore this phenomenon in each separate type of investment vehicle, namely stocks, US ETFs and cryptocurrencies, using the Cross-Sectional Absolute Deviation model. We find mostly similar herding patterns for stocks and US ETFs. Subsequently, the same experiment is implemented on a combination of all three investment vehicles. For a deeper investigation, we adopt…
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Taxonomy
TopicsBlockchain Technology Applications and Security · Banking stability, regulation, efficiency · Financial Markets and Investment Strategies
