Risk evaluation for ARCH-GARCH vs. RBF NN forecasting and SVR models: Application to high-frequency time series

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F15%3A%230005529" target="_blank" >RIV/47813059:19240/15:#0005529 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Risk evaluation for ARCH-GARCH vs. RBF NN forecasting and SVR models: Application to high-frequency time series
Original language description
The paper is concerned with measuring and assessment of risk reduction in managerial decision-making. In this paper, we consider the accuracy of forecasting models based on statistical (stochastic) methods and an intelligent methodology based on soft orgranular computing. The proposed intelligent approach is applied to the high frequency time series of BUX indexes. We found that it is possible to achieve significant risk reduction in managerial decision-making by applying intelligent forecasting modelsbased on information technologies. The statistical GARCH-class models can react to the good and bad news
Czech name
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Czech description
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Project
<a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Intelligent Systems and Decision Making for Risk Analysis and Crisis Response - Proceedings of the 4th International Conference on Risk Analysis and Crisis Response, RACR 2013
ISBN
9781138000193
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
567-573
Publisher name
Society for Risk Analysis
Place of publication
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Event location
Istanbul; Turkey
Event date
Jan 1, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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