OIL PRICE ESTIMATION BASED ON CHANGES IN DOLLAR-DENOMINATED ETFS: A MULTI-INSTRUMENT REGRESSION APPROACH (2025-2026)

Abstract

This paper provides a rigorous econometric estimation of West Texas Intermediate (WTI) crude oil spot prices by analyzing the price action of liquid, dollar-denominated Exchange-Traded Funds (ETFs). Utilizing a high-frequency weekly dataset spanning March 2025 to March 2026, the study employs a series of linear regression models to ascertain the "Theoretical Spot Price" of crude oil. By treating WTI futures as the dependent variable and a basket of ETFs—including USO, BNO, USL, DBO, XLE, and XOP—as independent variables, we quantify the degree to which financialized energy assets leadingly reflect physical market fundamentals. The primary finding reveals a significant divergence between the actual spot price (96.09) and the model’s theoretical estimate of 99.10 for the week ending March 15, 2026. This $99.10 figure, derived specifically from the United States 12 Month Oil Fund (USL) regression, indicates an "Undervalued Spot" condition of 3.1%. The model achieved a statistical significance (p-value) of 0.031 (3.1%), suggesting that the ETF basket provides a robust explanatory framework for pricing discovery during periods of high volatility. The results suggest that institutional investors can utilize the "laddered" futures exposure of USL and the "optimum yield" strategies of DBO to mitigate contango-induced tracking errors and identify alpha-generating price lags in the physical market.