Comparing neural networks with other predictive models in artificial stock market
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F12%3A10130827" target="_blank" >RIV/00216208:11320/12:10130827 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Comparing neural networks with other predictive models in artificial stock market
Original language description
A new way of comparing models for forecasting was created. The confronted models are neural networks (feed-forward neural networks and Elman's simple recurrent neural networks), ARMA models (AR and ARMA), random forecast, a trivial forecast of future value by the last known value and moving average forecast. winning model is the one which earns the most money.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GBP402%2F12%2FG097" target="_blank" >GBP402/12/G097: DYME-Dynamic Models in Economics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Mathematical Methods in Economics 2012 Proceedings
ISBN
978-80-7248-779-0
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
502-507
Publisher name
Silesian University in Opava
Place of publication
Karviná
Event location
Karviná
Event date
Sep 11, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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