Asymmetric impact of energy prices on financial cycles based on interval time series modeling

Energy prices crucially affect financial cycles. We employ the bivariate empirical mode decomposition (BEMD) model to disaggregate the daily interval data of the volatility index (VIX) and rely on the threshold autoregressive interval model (TARI) to incorporate energy prices into the forecasting model. Furthermore, the threshold interval decomposition ensemble (TIDE) is used to forecast the VIX series with nonlinearities to improve the forecasting accuracy. Moreover, we apply the root mean square error (RMSE) and the Diebold–Mariano test (DM) to evaluate the TIDE model performance across various frequency components and the final integration results. This paper demonstrates a significant correlation between energy prices and financial cycles, along with a temporal asymmetry effect. While the impact of energy prices on improving VIX forecasting is minimal in the short term, it becomes substantial over medium and long terms. Specifically, the influence of liquefied petroleum gas (LPG) prices on the VIX is notable in both medium and long terms. Our results offer new insights and methodologies for predicting financial cycles, assisting investors in evaluating volatility-related exchange-traded products. Additionally, these findings are crucial for developing more effective policies to promote green energy development.