Predictive Power of Logistic Regression in Cryptocurrency Price Analysis

The surge of interest in cryptocurrencies, particularly Bitcoin, has spurred extensive research into understanding its price dynamics. In this study, we delve into the predictive power of Logistic Regression (LR) models for analyzing Bitcoin price movements. Leveraging historical data spanning several years, we employ LR techniques to discern the binary nature of Bitcoin price changes, whether they increase or decrease within a specified timeframe. Our analysis yields promising results, demonstrating that LR models effectively capture significant trends and patterns in Bitcoin price fluctuations. We discuss the implications of our findings for investors, traders, and policymakers, underscoring LR’s potential as a valuable tool for forecasting Bitcoin price movements and mitigating associated risks. By providing insights into the predictive capabilities of LR, our study contributes to the growing body of research aimed at enhancing understanding and decision-making in the dynamic cryptocurrency market landscape.