Term Structure and Risk Premiums of Commodity Futures With Linear Regressions
用基于回归的仿射期限结构模型估计商品期货的期限结构，该模型算法简单快速，能处理多种可观测和不可观测因子，并适用于日度甚至实时数据。结果发现模型能很好捕捉不同期限的时间序列变化和特定月份的截面变化，并揭示了不同风险因子对现货和期限溢价的不同解释力。
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.