An Empirical Analysis on ARIMA and Regression Models for Time Series Forecasting on Bitcoin Dataset

Abstract

n the rapidly evolving world of cryptocurrency markets, the precise forecasting of Bitcoin's value against the US Dollar acquires paramount importance, catering to the interests of diverse stakeholders including investors, regulatory agencies, and academia. This study ventures into a comprehensive assessment of various time series forecasting methodologies, including but not limited to Random Forest Regression, ARIMA, Linear Regression, and XGBoost. Notably, our investigation unveils a pivotal revelation: the foundational models like Linear Regression and Random Forest Regression, traditionally con-sidered less complex, not only contend but also surpass the forecast accuracy of ARIMA models in the realm of Bitcoin. This paper aims to demystify the underpinnings of this superior performance, especially in mitigating the inherent volatility and unpredictability characteristic of Bitcoin. Our findings herald a transformative perspective in financial time series forecasting, potentially reshaping investment strategies and predictive analytics in the digital currency landscape.n the rapidly evolving world of cryptocurrency markets, the precise forecasting of Bitcoin's value against the US Dollar acquires paramount importance, catering to the interests of diverse stakeholders including investors, regulatory agencies, and academia. This study ventures into a comprehensive assessment of various time series forecasting methodologies, including but not limited to Random Forest Regression, ARIMA, Linear Regression, and XGBoost. Notably, our investigation unveils a pivotal revelation: the foundational models like Linear Regression and Random Forest Regression, traditionally considered less complex, not only contend but also surpass the forecast accuracy of ARIMA models in the realm of Bitcoin. This paper aims to demystify the underpinnings of this superior performance, especially in mitigating the inherent volatility and unpredictability characteristic of Bitcoin. Our findings herald a transformative perspective in financial time series forecasting, potentially reshaping investment strategies and predictive analytics in the digital currency landscape.I