Risk-Neutral Skewness and Commodity Futures Pricing
Research by Ana-Maria Fuertes, Ph.D., Bayes Business School, City, University of London, U.K. and Associate Editor of the GCARD; Zhenya Liu, Ph.D., Renmin University, China; and Weiqing Tang, Ph.D., Senior Quantitative Risk Management Associate, CME Group Inc., U.K.
This paper investigates the predictive content of a risk-neutral skewness (RNSK) signal for the dynamics of commodity futures prices. A trading strategy that buys futures with positive RNSK and sells futures with negative RNSK generates a significant excess return, which suggests a positive RNSK-return nexus. The risk premia that can be extracted through the RNSK signal is more pronounced in the contango than backwardation phase. After accounting for traditional commodity futures predictors, the RNSK signal exhibits a relatively stable and prolonged predictive ability. The directional-learning hypothesis is able to rationalize the positive nexus in terms of arbitrage risks and illiquidity (positive RNSK) and overpricing (negative RNSK).
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