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Research on Herding Effect in Emergencies

Song, Minrui LU and Cui, Can LU (2020) NEKN02 20201
Department 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.
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author
Song, Minrui LU and Cui, Can LU
supervisor
organization
course
NEKN02 20201
year
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}},
}