Beyond the FF6: Pricing Anomalies in Commodity-Linked ETFs
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Title:Beyond the FF6: Pricing Anomalies in Commodity-Linked ETFsAuthor:Scott Matthew Brown, University of Puerto Rico (scott.brown@upr.edu) Description:This dataset and associated paper investigate the limitations of the Fama-French 6-factor (FF6) model when applied to commodity-linked exchange-traded funds (ETFs). Using daily return data from 2010 to 2024 for GLD (gold), SLV (silver), USO (oil), and WEAT (wheat), alongside SPY (S&P 500), we conduct asset pricing regressions corrected with Newey-West standard errors. The results show that while FF6 explains equity returns well (SPY adj. R² ≈ 0.99), it fails to capture the return dynamics of commodity ETFs, which exhibit low adjusted R² values and statistically weak or insignificant factor exposures—especially for value, profitability, and investment factors. Additional regressions on bond ETFs (LQD, SPTL) reinforce the bounded applicability of equity-based factor models. Robustness checks using subsample splits, illiquidity controls, and alternative specifications (APT and commodity-augmented models) confirm the persistence of pricing anomalies. This research highlights the need for domain-specific asset pricing models that incorporate commodity market structure, roll yield, and inventory dynamics. Keywords:Fama-French 6-Factor Model, Commodity ETFs, Pricing Anomalies, Roll Yield, Newey-West, Liquidity, COVID-19, SPY, GLD, SLV, USO, WEAT, Structural Risk, Portfolio Diversification License:CC-BY 4.0 International
