Abstract
In the recent time as well as the last decade cryptocurrency has been one of the most discussed topic among the researchers all around the world. Different economies across the globe have seen a lot of growth of cryptocurrency over the time and bitcoin especially has seen a growth of 1100% that is why time series analysis of cryptocurrency is of immense significance. Time series analysis can be referred to as the process of taking into consideration a sequence of different points which are observed over a specific time interval. A large number of people start investing into cryptocurrencies without having any knowledge or analyzing the cryptocurrency market because of the hype it has these days and suffer huge losses so designing a model which can predict accurately as to how different cryptocurrencies would behave on basis of previous record can be very helpful and it can help some people in making profit rather than suffering loss. This paper presents a comparative overview of different algorithms like RNN, Linear Regression, GARCH, and ARIMA which can be used for time series analysis and concludes as to which algorithm is best suitable for time series analysis by considering different parameters like RMSE, MAE, etc., Besides this, it also analyzes the different factors which affect the prices of cryptocurrency.
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Sejwal, S., Aggarwal, K., Nayak, S.R., Awotunde, J.B. (2023). Time Series Analysis of Cryptocurrency: Factors and Its Prospective. In: Dhar, S., Do, DT., Sur, S.N., Liu, H.CM. (eds) Advances in Communication, Devices and Networking. Lecture Notes in Electrical Engineering, vol 902. Springer, Singapore. https://doi.org/10.1007/978-981-19-2004-2_22
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