bibtype J - Journal Article
ARLID 0361537
utime 20240103195407.2
mtime 20110913235959.9
title (primary) (eng) Comparing Neural Networks and ARMA Models in Artificial Stock Market
specification
page_count 13 s.
serial
ARLID cav_un_epca*0293025
ISSN 1212-074X
title Bulletin of the Czech Econometric Society
volume_id 18
volume 28 (2011)
page_num 53-65
keyword neural networks
keyword vector ARMA
keyword artificial market
author (primary)
ARLID cav_un_auth*0256729
name1 Krtek
name2 Jiří
full_dept (cz) Ekonometrie
full_dept (eng) Department of Econometrics
department (cz) E
department (eng) E
institution UTIA-B
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101230
name1 Vošvrda
name2 Miloslav
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/2011/E/krtek-comparing neural networks and arma models in artificial stock market.pdf
cas_special
project
project_id GD402/09/H045
agency GA ČR
ARLID cav_un_auth*0253998
research CEZ:AV0Z10750506
abstract (eng) Neural networks - feed-forward neural networks and Elman's simple recurrent neural networks - are compared with vector ARMA models - VAR and VARMA - in this paper. They are compared in anartifical stock market. One risk free and one risky asset are traded in the market. There are only trend followers in this model, which use the mentioned models for forecasting change of a price of the risky asset and the dividend. traded in the market
reportyear 2012
RIV AH
num_of_auth 2
permalink http://hdl.handle.net/11104/0198831
arlyear 2011
mrcbU63 cav_un_epca*0293025 Bulletin of the Czech Econometric Society 1212-074X Roč. 18 č. 28 2011 53 65