D. K, Baby Shamini P, Divya J, Indhumathi C, A. R.
{"title":"Cryptocurrency Exchange Rate Prediction using ARIMA Model on Real Time Data","authors":"D. K, Baby Shamini P, Divya J, Indhumathi C, A. R.","doi":"10.1109/ICEARS53579.2022.9751925","DOIUrl":null,"url":null,"abstract":"One of the most valuable currency across the globe right now is Cryptocurrency. Apart from being highly valued, its value increased from approximately 1 dollar in 2010 to 57521,576 in 2021 (for Bitcoin). Again, in recent years, it has attracted considerable attention in a variety of fields, including economics and computer science. The former focuses on studies to determine price fluctuations and its future prices for factors that determine how it will affect the market. The latter mainly focuses on its vulnerabilities, scalability and other techno-cryptocurrency issues. Its aim is to reveal the advantage of the traditional Autoregressive Integrative Moving Average (ARIMA) model in estimating the future value of cryptocurrency by analysing the price time series over a period of 3 years. On one hand, the factual studies show that the conduct of the time series is nearly unchanged, this simple scheme is efficient in sub-periods for the most part when it is used for short-term prediction, the further investigation in Cryptocurrency prediction of the price using an ARIMA model which has been trained over the whole dataset, as well as a limited part of the history of the Cryptocurrency price, with the input of length being w. The interaction of the prediction accuracy and choice of window size is well highlighted in the work.","PeriodicalId":252961,"journal":{"name":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","volume":"79 11-12","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEARS53579.2022.9751925","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
One of the most valuable currency across the globe right now is Cryptocurrency. Apart from being highly valued, its value increased from approximately 1 dollar in 2010 to 57521,576 in 2021 (for Bitcoin). Again, in recent years, it has attracted considerable attention in a variety of fields, including economics and computer science. The former focuses on studies to determine price fluctuations and its future prices for factors that determine how it will affect the market. The latter mainly focuses on its vulnerabilities, scalability and other techno-cryptocurrency issues. Its aim is to reveal the advantage of the traditional Autoregressive Integrative Moving Average (ARIMA) model in estimating the future value of cryptocurrency by analysing the price time series over a period of 3 years. On one hand, the factual studies show that the conduct of the time series is nearly unchanged, this simple scheme is efficient in sub-periods for the most part when it is used for short-term prediction, the further investigation in Cryptocurrency prediction of the price using an ARIMA model which has been trained over the whole dataset, as well as a limited part of the history of the Cryptocurrency price, with the input of length being w. The interaction of the prediction accuracy and choice of window size is well highlighted in the work.