Testing for herding in the cryptocurrency market

By Antonis Ballis, Konstantinos Drakos. 2020

133 citations recorded by the source corpus.

Abstract The study investigates whether herding behavior is present in the rapidly emerging cryptocurrency market. By analyzing daily data from major cryptocurrencies during the period August 2015 to December 2018, we find evidence that investors in the cryptocurrency market act irrationally and imitate other's decisions with no reference to their own beliefs. Furthermore, our empirical results provide evidence that the up-events market dispersion follows market movements at a faster pace compared to the down events. Thus, cryptocurrencies show a behavior where they tend to move in tandem, which does not necessarily reflect their fundamentals.

Subfields: Economics and Econometrics, Information Systems

View Paper: https://www.semanticscholar.org/paper/b365b8b8321143fca9fc965f016306453ccb5679

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Ender Demir
2. Conrado Diego García‐Gómez
3. Chi Keung Marco Lau
4. S. Simonyan
5. Giray Gozgor
6. Ahmet Sensoy

In Information Systems

1. Ender Demir
2. Conrado Diego García‐Gómez
3. Chi Keung Marco Lau
4. S. Simonyan
5. Ahmet Sensoy

Citations in the corpus

• The asymmetric effect of bitcoin on altcoins: evidence from the nonlinear autoregressive distributed lag (NARDL) model (2020, background): “Following Bitcoin, around 2,000 cryptocurrencies have been released and most of them are traded in international markets (Ballis and Drakos, 2019).”