Statistical/RBF NN framework for high frequency financial data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F21%3A10249575" target="_blank" >RIV/61989100:27510/21:10249575 - isvavai.cz</a>
Result on the web
<a href="https://www.ekf.vsb.cz/smsis/en/proceedings/past-proceedings/" target="_blank" >https://www.ekf.vsb.cz/smsis/en/proceedings/past-proceedings/</a>
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
Statistical/RBF NN framework for high frequency financial data
Original language description
In this paper, we develop and consider the accuracy of forecasting models based on statistical (stochastic) methods and two intelligent methodology based on SVM approach and neural networks by using novel activation function based on the cloud concept with parameters chosen by a grid search. The use of both intelligent methods is useful because there is no knowledge about the relationship between the inputs into the system and its output. The proposed approaches are applied to predict the high frequency time series of the daily EUR/USD exchange rate time series and assess their prediction performance. We showed that intelligent learning methods have more accurate outputs than the statistical one. On the other hand, the statistical GARCH-class models can identify the presence of the leverage effect and to react to the good and bad news. (C) Proceedings of the 14th International Conference on Strategic Management and its Support by Information Systems 2021, SMSIS 2021.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 14th International Conference Strategic Management and its Support by Information Systems 2021: May 25-26, 2021, Ostrava, Czech Republic
ISBN
978-80-248-4521-0
ISSN
2570-5776
e-ISSN
—
Number of pages
10
Pages from-to
178-187
Publisher name
VŠB - Technical University of Ostrava
Place of publication
Ostrava
Event location
Ostrava
Event date
May 25, 2021
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
—