Term Structure and Risk Premiums of Commodity Futures With Linear Regressions

Abstract

We apply the regression-based affine term structure model to estimate the term structure of commodity futures. This model is advantageous in that it has a simple and fast algorithm, can accommodate a variety of observable and unspanned factors, and can be applied to daily and even real-time observations. The results show that the model appropriately captures time-series variations across different maturities and exhibits satisfactory performance in capturing cross-sectional variations for specific months. Furthermore, we investigate the relationship between the existing commodity risk factor returns and the risk premiums inferred by the model. Our analysis reveals that different risk factor returns explain the spot and term premiums differently. Therefore, using the advantages of the model, we can better understand the term structure and risk premiums in commodity futures.