Understanding the Volatility of Bitcoin Returns: Dynamic Estimation and Predictive Analysis Based on Specific GARCH Approaches

In the financial sphere, volatility is a key factor. This study aims to analyse and predict the volatility associated with Bitcoin’s daily returns between January 2019 and August 2025. Using the GARCH (1,1) autoregressive model sequentially with normal, Student’s t and generalised error (GE) distributions in sequence demonstrates an understanding of the volatility transmission mechanism of this innovative financial asset within the context of the complex investment process. The empirical evidence obtained indicates a tendency for negative daily Bitcoin returns, reflecting persistent and high volatility during the analysed period. Furthermore, predictive analysis suggests that this high volatility is due to economic and financial uncertainty caused by the pandemic, high inflation rates, and the war between Russia and Ukraine. Conversely, predictive analysis shows that Bitcoin is becoming a risk diversification option and is currently playing the role of a risk diversifier, targeting long-term reverse volatility of approximately 4.89%. Finally, the study emphasises that investors are paying much closer attention to, and are much more concerned about, changes in the cryptocurrency market.