This study examines daily prices, returns, and volatility risk of the OPEC Basket over a 5640-day period from March 1, 2003, to November 13, 2024. Various statistical models, including Haar, D4, La8, Bl14, and C6, are utilized to predict prices, returns, and volatility risk. The results show that the Haar model outperforms the other models in predicting OPEC Basket Prices, based on error metrics such as RMSE, MAE, MPE, MAPE, MASE, and ACF1. Additionally, the Haar model also demonstrates superior performance in predicting volatility risk, with lower error values across these same metrics except ACF1. For returns, both the Haar and D4 models outperform the other models based on RMSE, MAE, MASE, and ACF1. These findings are significant as they provide critical insights for investors and stakeholders in the oil market. Accurate price prediction is essential for strategic decision-making, and volatility risk assessment helps stakeholders manage risk exposure. The superior performance of the Haar model for both price and volatility predictions indicates its potential use as a reliable tool for forecasting in the oil market. The consistent results from the D4 model for return predictions further enhance the robustness of the findings, offering an additional method for risk management. By improving predictive accuracy, these models can help investors make better-informed decisions, mitigate potential losses, and optimize investments in a highly volatile market like oil.