{"title":"Bitcoin Price Prediction Using Autoregressive Integrated Moving Average (ARIMA) Model","authors":"Chunyu Wen, Tianer Li, Zhiyang Qiu","doi":"10.1145/3573834.3574559","DOIUrl":null,"url":null,"abstract":"As the world's most valuable cryptocurrency, Bitcoin offers a new opportunity for price forecasting because of its high volatility, which is much higher compared to traditional currencies. Since bitcoin prices fluctuate randomly over time, we can use a time series model to predict the price of bitcoin. For this purpose, we use the ARIMA model to predict the future bitcoin price based on past prices. The basic idea of the ARIMA model is that the data series of the predicted object over time is considered as a random series, and some mathematical model is used to approximate this series. Once this model is determined, it is possible to predict the future values from the past values of the time series as well as the present values. The model achieves high accuracy and robustness. The result shows that there's inevitable deviation every time the price trend is having acute change, and the deviation of actual value to predicted one is positively correlated to the average value.","PeriodicalId":345434,"journal":{"name":"Proceedings of the 4th International Conference on Advanced Information Science and System","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 4th International Conference on Advanced Information Science and System","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3573834.3574559","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
As the world's most valuable cryptocurrency, Bitcoin offers a new opportunity for price forecasting because of its high volatility, which is much higher compared to traditional currencies. Since bitcoin prices fluctuate randomly over time, we can use a time series model to predict the price of bitcoin. For this purpose, we use the ARIMA model to predict the future bitcoin price based on past prices. The basic idea of the ARIMA model is that the data series of the predicted object over time is considered as a random series, and some mathematical model is used to approximate this series. Once this model is determined, it is possible to predict the future values from the past values of the time series as well as the present values. The model achieves high accuracy and robustness. The result shows that there's inevitable deviation every time the price trend is having acute change, and the deviation of actual value to predicted one is positively correlated to the average value.