A new grey system approach to forecast closing price of Bitcoin, Bionic, Cardano, Dogecoin, Ethereum, XRP Cryptocurrencies
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Social Sciences,Statistics and Probability
Link
https://link.springer.com/content/pdf/10.1007/s11135-022-01463-0.pdf
Reference72 articles.
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2. Aggarwal, A., Gupta, I., Garg, N., and Goel, A.: Deep learning approach to dtermine the impact of socio economic factors on bitcoin price prediction. In: 2019 Twelfth International Conference on Contemporary Computing (IC3), pp. 1–5. https://doi.org/10.1109/IC3.2019.8844928 (2019)
3. Agosto, A., Cafferata, A.: Financial bubbles: a study of co-explosivity in the cryptocurrency market. Risks 8(2), 34 (2020). https://doi.org/10.3390/risks8020034
4. Antonakakis, N., Chatziantoniou, I., Gabauer, D.: Cryptocurrency market contagion: market uncertainty, market complexity, and dynamic portfolios. J. Int. Financ. Markets. Inst. Money 61, 37–51 (2019). https://doi.org/10.1016/j.intfin.2019.02.003
5. Arsy, F.A.: Demand forecasting of Toyota Avanza cars in Indonesia: grey systems approach. Int. J. Grey Syst. 1(1), 38–47 (2021). https://doi.org/10.52812/ijgs.24
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