Predicting Macro-Economic Factors of WTI Crude Oil Using Monte Carlo Simulation

In this paper, we use regression equations and Monte Carlo simulations to study the dynamics of WTI crude oil prices. Our research takes the price of WTI crude oil as the dependent variable and looks at how it relates to nine key macroeconomic variables, most of which have to do with supply. We recognize the importance of these factors affecting the price of crude oil by using the knowledge from earlier studies. In order to make our study easier, we compile historical WTI crude oil price data from the last 60 months and combine it with the chosen macroeconomic indicators. The choice of the variables stem from their critical role in shaping crude oil markets. Through a multiple regression model, we aim to establish a comprehensive understanding of the dependencies between WTI crude oil prices and the macroeconomic factors. To ensure the robustness of our model, we assess multicollinearity among the independent variables, emphasizing that while they are related to WTI crude prices, they should not exhibit high intercorrelations. Our research provides a valuable framework for scenario generation, allowing us to explore potential future price movements based on the identical relationships. By unveiling the intricate interplay between these factors and WTI crude oil prices our study contributes to informed decision-making for investors and policymakers.