Research on Herding Effect in Emergencies
(2020) NEKN02 20201Department of Economics
- Abstract
- In this paper, herding effect among pandemic emergencies, natural disaster emergencies and terrorist attacks emergencies is studied. This paper uses quantile regression with the approach proposed by Chiang and Zheng (2010) to detect herding during the time period 2001-2020. In terms of event types, herding is captured in every event group. More specifically, the pandemic group shows the most significant evidence of herding, the next is natural disaster group, and the last is the terrorist attack group. No evidence shows industries related to events are more likely to lead to herding, comparing with unrelated industries.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9015088
- author
- Song, Minrui LU and Cui, Can LU
- supervisor
- organization
- course
- NEKN02 20201
- year
- 2020
- type
- H1 - Master's Degree (One Year)
- subject
- keywords
- Behavioral finance, Herding effect, Cross-sectional absolute deviation, quantile regression
- language
- English
- id
- 9015088
- date added to LUP
- 2020-08-29 11:21:09
- date last changed
- 2020-08-29 11:21:09
@misc{9015088, abstract = {{In this paper, herding effect among pandemic emergencies, natural disaster emergencies and terrorist attacks emergencies is studied. This paper uses quantile regression with the approach proposed by Chiang and Zheng (2010) to detect herding during the time period 2001-2020. In terms of event types, herding is captured in every event group. More specifically, the pandemic group shows the most significant evidence of herding, the next is natural disaster group, and the last is the terrorist attack group. No evidence shows industries related to events are more likely to lead to herding, comparing with unrelated industries.}}, author = {{Song, Minrui and Cui, Can}}, language = {{eng}}, note = {{Student Paper}}, title = {{Research on Herding Effect in Emergencies}}, year = {{2020}}, }