Analyzing dynamics of crude oil price amid sudden events and intervention measures: Insights from a Prophet-QR model

Given that crude oil prices are influenced by the complex interplay of political, economic, and social events, leading to rapid, substantial, and unpredictable fluctuations, the associated risk has received considerable attention. How can we quantitatively characterize the impact of these sudden events and accurately measure crude oil price risk? To achieve this objective, the paper introduces the Prophet Quantile Regression (Prophet-QR) model. This model not only analyzes the impact of sudden events on crude oil prices but also evaluates the effectiveness of strategies implemented to control these fluctuations. It also forecasts the future distribution of crude oil prices and measures both the potential upside and downside risks associated with crude oil price volatility. By employing a multi-step ahead rolling forecasting approach and the proposed Prophet-QR model, this study draws several empirical conclusions. First, the Prophet-QR model demonstrates superior accuracy in prediction. Second, sudden events, such as the Iraq war and the Libyan war, have a profound impact on crude oil prices, causing the oil price at risk (OaR) to rise sharply. Third, the implementation of oil price intervention measures, such as production cuts and strategic reserve releases, is highly effective in mitigating the adverse effects of sudden events, thereby normalizing the OaR. Continuously monitoring OaR fluctuations supports informed policymaking and effectively reduces the adverse impacts of sudden events on future crude oil prices.