Abstract
ABSTRACTA latent‐factor model based on the instrumented principal component analysis (IPCA) methodology of Kelly et al. outperforms existing factor models in explaining cross‐sectional variations in commodity futures returns. The model allows for observed commodity futures characteristics to work as instruments for unobservable dynamic factor loadings. We find that the relationship between characteristics and commodity futures returns is driven by compensation for exposure to latent risk factors (beta) rather than compensation for exposure to mispricing (alpha). Three latent factors deliver more powerful explanations than any number of observable factors. Among a collection of 20 characteristics, only three are significantly related to latent factor betas. These three characteristics are momentum, expected shortfall, and idiosyncratic volatility.
Published Version
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