volatility assessment

Evening Bitcoin market trends exhibit distinct volatility patterns, offering opportunities for data-driven analysis and forecasting. Our research investigates the complex dynamics of these trends through statistical modeling and time series analysis. We employ advanced econometric techniques such as ARCH and GARCH models to capture volatility clustering and persistence. By analyzing historical data and implementing robust parameter estimation methods, we develop predictive models that quantify volatility risk and inform investment strategies. This study contributes to a deeper understanding of the Bitcoin market by providing insights into the drivers of evening volatility and enabling more accurate price forecasts.