Risk Premia in Crude Oil Futures Prices

Abstract

If commercial producers or financial investors use futures contracts to hedge against commodity price risk, the arbitrageurs who take the other side of the contracts may receive compensation for their assumption of nondiversifiable risk in the form of positive expected returns from their positions. We show that this interaction can produce an affine factor structure to commodity futures prices, and develop new algorithms for estimation of such models using unbalanced data sets in which the duration of observed contracts changes with each observation. We document significant changes in oil futures risk premia since 2005, with the compensation to the long position smaller on average in more recent data. This observation is consistent with the claim that index-fund investing has become more important relative to commerical hedging in determining the structure of crude oil futures risk premia over time.

A General Approach to Recovering Market Expectations from Futures Prices with an Application to Crude Oil

“…We then evaluate the merits of these estimates based on the predictive content of the implied oil price expectations. Based on the 2 MSPE ranking, the most accurate estimate of the expectation of the price of oil is obtained by adjusting the oil futures price by the risk premium inferred from the term-structure model of Hamilton and Wu (2014). This expectations measure not only is more accurate than any other estimate of the oil price expectation that we considered (including the unadjusted oil futures price), but also is economically more plausible.…”

Oil market modelling: A comparative analysis of fundamental and latent factor approaches

“…Such methodologies circumvent the need for the explicit identification of fundamental factors. Latent factor approaches have been used to capture the complex movement in commodity forward curves (Gibson and Schwartz, 1990, Schwartz, 1997, Casassus and CollinDufresne, 2005, Trolle and Schwartz, 2009, Casassus et al, 2013, Hamilton and Wu, 2014 and to forecast future oil prices (Cabbibo andFiorenzani, 2004, Chantziara andSkiadopoulos, 2008); much of the the former literature focused on derivatives pricing and risk management applications. Chantziara and Skiadopoulos (2008) argue that principal component analysis (PCA) provides a parsimonious, non-parametric methodology to describe commodity forward curve dynamics, and should contain full information on the underlying economic drivers of oil prices.…”

Learning in the Oil Futures Markets: Evidence and Macroeconomic Implications

“…In particular, our paper relates to some of the recent work on the role of financial markets in driving oil prices. 3 For instance, Hamilton and Wu (2014) Buyuksahin et al (2008) argue that increased market activity by commodity swap dealers, hedge funds, and other financial traders, has helped link crude oil futures prices at different maturities. Acharya et al (2013) emphasize limits to arbitrage and their effects on spot and futures prices in commodity markets.…”