Research background and purpose : The rise of Bitcoin has prompted significant interest and debate, yet a comprehensive understanding of its pricing dynamics remains elusive. This study aims to address this gap by investigating the factors driving Bitcoin's price. Methodology : Leveraging time-series data from December 19, 2016, to June 30, 2023, we employ the Auto-Regressive Distributed Lag (ARDL) model and cointegration test introduced by Pesaran et al. (2001) to analyze the impacts of various factors on Bitcoin's price. Findings : Our findings highlight the influential roles of demand and supply metrics, such as the number of addresses and circulating stock, as well as technological factors related to the Blockchain, including transaction costs, hash rate, and mining difficulty. Interestingly, we find limited correlations between macroeconomic or financial developments and Bitcoin's price. Value added and limitations : Our empirical findings validate the pivotal role of supply and demand dynamics in shaping Bitcoin prices, suggesting a degree of predictability corresponding to traditional currency pricing models. These findings underscore the complexity of Bitcoin's value dynamics and have implications for investors, policymakers, and researchers. Nevertheless, the study did not account for variables related to the appeal of Bitcoin as an asset class, nor did it explore the psychological aspects that could influence investor behavior. Therefore, it is likely that new determinants will arise in the future, demanding further exploration.