bibtype J - Journal Article
ARLID 0395344
utime 20240103202847.4
mtime 20130926235959.9
WOS 000326772200015
DOI 10.1016/j.physa.2013.07.050
title (primary) (eng) Behavioural breaks in the heterogeneous agent model: The impact of herding, overconfidence, and market sentiment
specification
page_count 19 s.
media_type P
serial
ARLID cav_un_epca*0257423
ISSN 0378-4371
title Physica. A : Statistical Mechanics and its Applications
volume_id 392
volume 23 (2013)
page_num 5920-5938
publisher
name Elsevier
keyword Heterogeneous agent model
keyword Behavioural finance
keyword Herding
keyword Overconfidence
keyword Market sentiment
keyword Stock market crash
author (primary)
ARLID cav_un_auth*0293468
name1 Kukačka
name2 Jiří
full_dept (cz) Ekonometrie
full_dept (eng) Department of Econometrics
department (cz) E
department (eng) E
institution UTIA-B
full_dept Department of Econometrics
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0242028
name1 Baruník
name2 Jozef
full_dept (cz) Ekonometrie
full_dept Department of Econometrics
department (cz) E
department E
institution UTIA-B
full_dept Department of Econometrics
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2013/E/barunik-0395344.pdf
cas_special
project
project_id GA402/09/0965
agency GA ČR
ARLID cav_un_auth*0253176
abstract (eng) The main aim of this work is to incorporate selected findings from behavioural finance into a Heterogeneous Agent Model using the Brock and Hommes (1998) [34] framework. Behavioural patterns are injected into an asset pricing framework through the so-called ‘Break Point Date’, which allows us to examine their direct impact. In particular, we analyse the dynamics of the model around the behavioural break. Price behaviour of 30 Dow Jones Industrial Average constituents covering five particularly turbulent US stock market periods reveals interesting patterns in this aspect. To replicate it, we apply numerical analysis using the Heterogeneous Agent Model extended with the selected findings from behavioural finance: herding, overconfidence, and market sentiment. We show that these behavioural breaks can be well modelled via the Heterogeneous Agent Model framework and they extend the original model considerably. Various modifications lead to significantly different results and model with behavioural breaks is also able to partially replicate price behaviour found in the data during turbulent stock market periods.
reportyear 2014
RIV AH
num_of_auth 2
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0223482
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mrcbU34 000326772200015 WOS
mrcbU63 cav_un_epca*0257423 Physica. A : Statistical Mechanics and its Applications 0378-4371 1873-2119 Roč. 392 č. 23 2013 5920 5938 Elsevier