Modeling of the Bitcoin Volatility through Key Financial Environment Variables: An Application of Conditional Correlation MGARCH Models

Since the launch of Bitcoin, there has been a lot controversy surrounding what asset class it is. Several authors recognize potential cryptocurrencies but also certain deviations with respect to functions conventional currency. Instead, Bitcoin’s diversifying factor and its high return have generated attention portfolio managers. In this context, understanding how volatility is explained critical element investor decision-making. By modeling classic assets, nonlinear models such as Generalized Autoregressive Conditional Heteroskedasticity (GARCH) offer suitable results. Therefore, taking GARCH(1,1) reference point, main aim study model assess relationship between Bitcoin key financial environment variables through Correlation (CC) Multivariate GARCH (MGARCH) approach. For this, several commodities, exchange rates, stock market indices, company stocks linked tested. The results obtained show heterogeneity in fit different variables, highlighting uncorrelation traditional safe haven assets gold oil. Focusing on CC-MGARCH model, better behavior dynamic conditional correlation found compared constant.