Cryptocurrency price prediction using ARIMA and ARIMAX models
DOI:
https://doi.org/10.24867/19BE08GlavasKeywords:
Cryptocurrencies, ARIMA, ARIMAXAbstract
This work discusses short and mid term price prediction of Dogecoin, Shiba Inu and Idena cryptocurrencies using ARIMA and ARIMAX models. Data was sampled from various publicly available sources, preprocessed to ensure stationarity and model parameters chosen with grid search and auto arima function. Different prediction intervals were tested and models evaluated using Akaike Infromation Criterion and mean average percent error. For short term predictions ARIMA model had error of about 3.5%, ARIMAX 7 to 19%. Both models proved inadequate for mid term predictions.
References
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[9] https://www.coingecko.com/ (pristupljeno u maju 2022.)
[10] https://trends.google.com/ (pristupljeno u maju 2022.)
[2] https://shibatoken.com/ (pristupljeno u maju 2022.)
[3] https://docs.idena.io/docs/wp/summary/ (pristupljeno u maju 2022.)
[4] Azari, Amin. "Bitcoin price prediction: An ARIMA approach." arXiv preprint arXiv:1904.05315 (2019).
[5] Scalzotto, Giovanni. "Social Media Impact on Cryptocurrencies." (2021).
[6] Peter, Ďurka, and Pastoreková Silvia. "ARIMA vs. ARIMAX–which approach is better to analyze and
forecast macroeconomic time series." Proceedings of 30th international conference mathematical methods in economics. Vol. 2. 2012.
[7] Mahan, Margaret & Chorn, Chelley & Georgopoulos, Apostolos. (2015). White Noise Test: detecting autocorrelation and nonstationarities in long time series after ARIMA modeling. 10.25080/Majora-7b98e3ed-00f.
[8] https://finance.yahoo.com/ (pristupljeno u maju 2022.)
[9] https://www.coingecko.com/ (pristupljeno u maju 2022.)
[10] https://trends.google.com/ (pristupljeno u maju 2022.)
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Published
2022-09-07
Issue
Section
Electrotechnical and Computer Engineering