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AI 2021, 2 495 9. Adams, R.; Kewell, B.; Parry, G. Blockchain for Good? Digital Ledger Technology and Sustainable Development Goals. In Handbook of Sustainability and Social Science Research; Filho, W.L., Marans, R., Callewaert, J., Eds.; World Sustainability Series; Springer: Cham, Switzerland, 2018. [CrossRef] 10. Killer, C.; Rodrigues, B.; Stiller, B. Security Management and Visualization in a Blockchain-based Collaborative Defense. In Proceedings of the ICBC 2019—IEEE International Conference on Blockchain and Cryptocurrency, Seoul, Korea, 14–17 May 2019; pp. 108–111. [CrossRef] 11. Gandal, N.; Halaburda, H. Competition in the Cryptocurrency Market (September 29, 2014). CESifo Working Paper Series No. 4980. Available online: https://ssrn.com/abstract=2506577 (accessed on 16 June 2021). 12. Iwamura, M.; Kitamura, Y.; Matsumoto, T. Is Bitcoin the Only Cryptocurrency in the Town? Economics of Cryptocurrency And Friedrich A. Hayek (February 28, 2014). Available online: https://ssrn.com/abstract=2405790 (accessed on 16 June 2021). [CrossRef] 13. Kyriazis, N.A. A Survey on Empirical Findings about Spillovers in Cryptocurrency Markets. J. Risk Financ. Manag. 2019, 12, 170. [CrossRef] 14. Hassani, H.; Huang, X.; Silva, E. Big-Crypto: Big Data, Blockchain and Cryptocurrency. Big Data Cogn. Comput. 2018, 2, 34. [CrossRef] 15. Nizzoli, L.; Tardelli, S.; Avvenuti, M.; Cresci, S.; Tesconi, M.; Ferrara, E. Charting the Landscape of Online Cryptocurrency Manipulation. IEEE Access 2020, 8, 113230–113245. [CrossRef] 16. Rebane, J.; Karlsson, I.; Papapetrou, P.; Denic, S. Seq2Seq RNNs and ARIMA models for Cryptocurrency Prediction: A Compara- tive Study. In Proceedings of the SIGKDD Workshop on Fintech (SIGKDD Fintech’18), London, UK, 19–23 August 2018. 17. Rehman, M.U.; Apergis, N. Determining the predictive power between cryptocurrencies and real time commodity futures: Evidence from quantile causality tests. Resour. Policy 2019, 61, 603–616. [CrossRef] 18. Liew, J.; Li, R.Z.; Budavári, T.; Sharma, A. Cryptocurrency Investing Examined. J. Br. Blockchain Assoc. 2019, 2, 1–12. [CrossRef] 19. Dyntu, V.; Dykyi, O. Cryptocurrency in the system of money laundering. Balt. J. Econ. Stud. 2019, 4, 75–81. [CrossRef] 20. Kethineni, S.; Cao, Y. The Rise in Popularity of Cryptocurrency and Associated Criminal Activity. Int. Crim. Justice Rev. 2019, 30, 325–344. [CrossRef] 21. Liu, Y.; Tsyvinski, A. Risks and Returns of Cryptocurrency. Rev. Financ. Stud. 2020, 34, 2689–2727. [CrossRef] 22. Valdeolmillos, D.; Mezquita, Y.; González-Briones, A.; Prieto, J.; Corchado, J.M. Blockchain Technology: A Review of the Current Challenges of Cryptocurrency. In Blockchain and Applications. BLOCKCHAIN 2019. Advances in Intelligent Systems and Computing; Prieto, J., Das, A., Ferretti, S., Pinto, A., Corchado, J., Eds.; Springer: Cham, Switzerland, 2020; Volume 1010. [CrossRef] 23. Yuneline, M.H. Analysis of cryptocurrency’s characteristics in four perspectives. J. Asian Bus. Econ. Stud. 2019, 26, 206–219. [CrossRef] 24. Huynh, T.L.D.; Nasir, M.A.; Vo, X.V.; Nguyen, T.T. “Small things matter most”: The spillover effects in the cryptocurrency market and gold as a silver bullet. North Am. J. Econ. Financ. 2020, 54, 101277. [CrossRef] 25. Hitam, N.A.; Ismail, A.R. Comparative Performance of Machine Learning Algorithms for Cryptocurrency Forecasting. Indones. J. Electr. Eng. Comput. Sci. 2018, 11, 1121–1128. [CrossRef] 26. Andrianto, Y. The Effect of Cryptocurrency on Investment Portfolio Effectiveness. J. Financ. Account. 2017, 5, 229. [CrossRef] 27. Derbentsev, V.; Babenko, V.; Khrustalev, K.; Obruch, H.; Khrustalova, S. Comparative Performance of Machine Learning Ensemble Algorithms for Forecasting Cryptocurrency Prices. Int. J. Eng. Trans. A Basics 2021, 34, 140–148. [CrossRef] 28. Patel, M.M.; Tanwar, S.; Gupta, R.; Kumar, N. A Deep Learning-based Cryptocurrency Price Prediction Scheme for Financial Institutions. J. Inf. Secur. Appl. 2020, 55, 102583. [CrossRef] 29. Miura, R.; Pichl, L.; Kaizoji, T. Artificial Neural Networks for Realized Volatility Prediction in Cryptocurrency Time Series. In Advances in Neural Networks—ISNN 2019; Lu, H., Tang, H., Wang, Z., Eds.; Lecture Notes in Computer Science; Springer: Cham, Switzerland, 2019; Volume 11554. [CrossRef] 30. Karasu, S.; Altan, A.; Sarac, Z.; Hacioglu, R. Prediction of Bitcoin prices with machine learning methods using time series data. In Proceedings of the 26th Signal Processing and Communications Applications Conference (SIU), Izmir, Turkey, 2–5 May 2018. [CrossRef] 31. Saad, M.; Mohaisen, A. Towards characterizing blockchain-based cryptocurrencies for highly-accurate predictions. In Proceedings of the IEEE INFOCOM—IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Honolulu, HI, USA, 15–19 April 2018. [CrossRef] 32. Yiying, W.; Yeze, Z. Cryptocurrency Price Analysis with Artificial Intelligence. In Proceedings of the 5th International Conference on Information Management (ICIM), Cambridge, UK, 24–27 March 2019; pp. 97–101. [CrossRef] 33. Chen, Z.; Li, C.; Sun, W. Bitcoin price prediction using machine learning: An approach to sample dimension engineering. J. Comput. Appl. Math. 2019, 365, 112395. [CrossRef] 34. Valencia, F.; Gómez-Espinosa, A.; Valdés-Aguirre, B. Price Movement Prediction of Cryptocurrencies Using Sentiment Analysis and Machine Learning. Entropy 2019, 21, 589. [CrossRef] 35. Ferdiansyah, F.; Othman, S.H.; Radzi, R.Z.R.M.; Stiawan, D.; Sazaki, Y.; Ependi, U. A LSTM-Method for Bitcoin Price Prediction: A Case Study Yahoo Finance Stock Market. In Proceedings of the ICECOS—3rd International Conference on Electrical Engineering and Computer Science, Batam, Indonesia, 2–3 October 2019; pp. 206–210. [CrossRef]PDF Image | Novel Cryptocurrency Price Prediction Model Using GRU
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