Use this url to cite publication: https://hdl.handle.net/20.500.12259/102058
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Cryptocurrencies short-term forecast: application of ARIMA, GARCH and SVR models
Type of publication
Straipsnis konferencijos medžiagoje Scopus duomenų bazėje / Article in conference proceedings in Scopus database (P1a2)
Author(s)
LT | ||||
LT | ||||
LT | Baltijos pažangių technologijų institutas, Vilnius | LT |
Title
Cryptocurrencies short-term forecast: application of ARIMA, GARCH and SVR models
Is part of
CEUR Workshop proceedings [electronic resource]: IVUS 2019, International conference on information technologies, Kaunas, Lithuania, 25 April, 2019. Aachen : CEUR-WS, 2019, Vol. 2470
Date Issued
Date Issued |
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2019 |
Publisher
Aachen : CEUR-WS
Is Referenced by
Extent
p. 70-73
Field of Science
Abstract
Cryptocurrency are difficult to forecast due to it’s globality and availability to everyone and every time. There is no Friday or Holidays effect, seasonality, market news and other aspects, which influence the course direction. It is the phenomena of the market and it is useful to spread forecast methods research to find out the best fitting model for this phenomenon. In this paper is presented short-term forecast of five different cryptocurrencies (Bitcoin, BitcoinCash, Ethereum, Litecoin, Ripple). Forecast methods split in two groups: 1) real value (ARIMA and SVR models) 2) volatility (GARCH and SVR models). The model’s suitability is evaluated by RMSE and MAE. The best results for real value forecast were achieved using ARIMA, for volatility forecast - SVR. In further research it would be useful to analyze methods variety of Artificial Neural Networks and others connected models’ modifications.
Type of document
type::text::journal::journal article::research article
Language
Anglų / English (en)
Coverage Spatial
Vokietija / Germany (DE)