Artikel
A gated recurrent unit approach to bitcoin price prediction
In today's era of big data, deep learning and artificial intelligence have formed the backbone for cryptocurrency portfolio optimization. Researchers have investigated various state of the art machine learning models to predict Bitcoin price and volatility. Machine learning models like recurrent neural network (RNN) and long short-term memory (LSTM) have been shown to perform better than traditional time series models in cryptocurrency price prediction. However, very few studies have applied sequence models with robust feature engineering to predict future pricing. In this study, we investigate a framework with a set of advanced machine learning forecasting methods with a fixed set of exogenous and endogenous factors to predict daily Bitcoin prices. We study and compare different approaches using the root mean squared error (RMSE). Experimental results show that the gated recurring unit (GRU) model with recurrent dropout performs better than popular existing models. We also show that simple trading strategies, when implemented with our proposed GRU model and with proper learning, can lead to financial gain.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 13 ; Year: 2020 ; Issue: 2 ; Pages: 1-16 ; Basel: MDPI
- Klassifikation
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Wirtschaft
- Thema
-
artificial intelligence
Bitcoin
cryptocurrency
deep learning
neural networks
predictive model
risk management
time series analysis
trading strategy
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Dutta, Aniruddha
Kumar, Saket
Basu, Meheli
- Ereignis
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Veröffentlichung
- (wer)
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MDPI
- (wo)
-
Basel
- (wann)
-
2020
- DOI
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doi:10.3390/jrfm13020023
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:44 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Dutta, Aniruddha
- Kumar, Saket
- Basu, Meheli
- MDPI
Entstanden
- 2020
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