Investigating dynamic conditional correlation between crude oil and fuels in non-linear framework: The financial and economic role of structural breaks

To understand the crude oil volatility has been a challenge. The non-linear behavior, the skewed and leptokurtic returns, the presence of structural breaks and the constant political instability in suppliers' countries evidence the necessity of complex models to capture the market volatility. At the same time, crude oil is the raw material for several fuels such as jet fuel, gasoline, diesel and others, having a strong influence over their prices. Thus, this study aims to verify the presence of structural breaks in the volatility series and in the correlations between WTI return and the returns of Gasoline, Kerosene Jet Fuel, Diesel, Heating Oil, Propane and Natural Gas. To reach this objective, we identified which model presents the best fit to estimate the conditional mean between WTI and each fuel and we used a Copula–DCC–GARCH model to estimate the conditional volatility avoiding the frequently unrealistic presumptions of normality. Our main results indicate the necessity of a different model for each analyzed pair and the presence of at least one structural break in the conditional volatility and in the correlation between WTI and each fuel, usually preceded by a structural break in WTI return series.