Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Vol. 26, 20 December 2023
* Author to whom correspondence should be addressed.
The Bitcoin price was chosen as the research subject, and the observation period was set from January 2015 to September 2023. An ARIMA time series model was constructed to forecast the trading price. The results indicate that the optimal model for fitting the trading price is ARIMA (3, 2, 8). This model takes into account trends, seasonality, and other factors that may impact the price of Bitcoin. By analyzing the historical data, the model was able to accurately predict the short-term fluctuations in Bitcoin’s trading price. Based on this, short-term predictions were made for Bitcoin’s trading price in the next year. Recommendations were then provided by combining the forecast results with the economic development situation in the post-pandemic era. The recommendations suggest that Bitcoin has become a low-quality asset and is no longer suitable for diversifying one’s investment portfolio, but rather focus on the development of physical industries and adjust one’s investment portfolio in a timely manner.
Bitcoin, ARIMA, financial modeling, cryptocurrency, time series analysis.
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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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