the co-movement between bitcoin, gold, usd and oil: dcc-garch and smooth transition regression (str) model

This study investigates the relationships between bitcoin (btc) prices and fluctuations in relation to gold, usd, and iran's oil prices from 2019 to 2022. we employed the dynamic conditional correlation generalized autoregressive conditional heteroscedasticity (dcc-garch) method to model the fluctua-tions of financial variables. additionally, the smooth transition regression (str) method was applied to explore the relationships between the variables. the results reveal significant positive correlations between btc prices and gold, as well as oil, and a negative correlation with usd prices. we observed volatility persistence, causality, and phase differences between btc and other financial instruments and indicators. notably, a negative relationship was identified between bitcoin and the usd in both linear and non-linear aspects, with a larger coefficient in the second regime. furthermore, a posi-tive relationship was found between bitcoin and the variables of gold and oil prices, with coefficients being larger in the second regime compared to the first.