We develop a framework to estimate time-varying commodity risk premia from multi-factor models using futures prices and analysts’ forecasts of future prices. The model is calibrated for oil using a 3-factor stochastic commodity-pricing model with an affine risk premia specification. The WTI oil futures price data is from the New York Mercantile Exchange (NYMEX) and analysts’ forecasts are from Bloomberg and the U.S Energy Information Administration. Weekly estimations for short, medium, and long-term risk premia between 2010 and 2017 are obtained. Results from the model calibration show that the term structure of oil risk premia moves stochastically through time, that short-term risk premia tend to be higher than long-term ones and that risk premia volatility is much higher for short maturities. An empirical analysis is performed to explore the macroeconomic and oil market variables that may explain the stochastic behavior of oil risk premia, showing that inventories, hedging pressure, term premium, default premium and the level of interest rates all play a significant role in explaining the risk premia.
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