Date of Award


Degree Type

Doctoral Dissertation

Degree Name

Doctor of Business Administration (DBA)


Jack Welch College of Business


Submitted in partial fulfillment of the requirements for the degree of Doctor of Business Administration in Finance, Sacred Heart University, Jack Welch College of Business and Technology.

Dissertation Supervisor

Dr. Lorán Chollete

Committee Member

Dr. Yaseen S. Alhaj Yaseen

Committee Member

Dr. Weijia Peng


This paper examines herd behavior in the cryptocurrency market using data of the top 15 large cryptocurrencies and the CCi30 Index as a proxy for market return. The idea that investors mimic and follow the behavior of others in the cryptocurrency market rather than conducting their own research has received attention in the finance literature. The CSAD results in the static model detected herding but given the existence of structural breakdowns and nonlinearities in the data series, we opted to conduct a rolling window analysis. The results indicate strong herding behavior that fluctuates over time. Furthermore, results from the logistic regression reveals that herding develops as uncertainty increases. Our findings are consistent with earlier research on identifying herding behavior in cryptocurrencies. It is an attempt to shed light on portfolio and risk management, trading strategies, and market efficiency.

JEL Classification

C 22, G14, G15, G40

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.



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