Skewness Effect in Commodities

Recent theoretical literature argues that total skewness matters to the pricing of assets, assets with higher degrees of skewness or lottery-like features should earn lower expected returns. Impact of skewness on asset's future returns has been investigated mainly for equities and options but researches are moving to review also other assets. A recent article by Perez, Frijns, Fuertes and Miffre studies the pricing of skewness in commodity futures markets. The time-series tests show that a fully-collateralized portfolio that buys commodities with low skewness and shorts commodities with high skewness earns 8.01% a year with a t-statistic of 4.08 and the performance of the low-minus-high skewness portfolio is not fully explained by a standard commodity benchmarks which makes it perfect addition into commodity based multi-strategy portfolios.

Fundamental reason

Academic studies explain skewness effect in all assed by investors are willing to pay a higher price, and to earn a lower expected return, on assets with lottery-like payoffs. By showing that skewness affects commodity futures returns, study documents that skewness is priced in markets other than the ones where retail investors typically trade. Hence, its findings suggests that the effect of skewness on asset returns is not merely a consequence of retail investor preferences. Rather this indicates that there are other groups of traders who have these heterogeneous preferences.

Markets traded
commodities
Confidence in anomaly's validity
Strong
Notes to Confidence in anomaly's validity
Period of rebalancing
Monthly
Notes to Period of rebalancing
Number of traded instruments
10
Notes to Number of traded instruments
Complexity evaluation
Simple strategy
Notes to Complexity evaluation
Financial instruments
futures, CFDs
Backtest period from source paper
1987-2014
Indicative performance
8.01%
Notes to Indicative performance
per annum, data from table 3 for long-short portfolio
Estimated volatility
10.20%
Notes to Estimated volatility
data from table 3 for long-short portfolio
Maximum drawdown
-29.73%
Notes to Maximum drawdown
data from table 3 for long-short portfolio
Sharpe Ratio
0.79

Keywords:

volatility effect

Simple trading strategy

The investment universe consists of 27 futures contracts on commodities. Each month, investor calculates skewness (3rd moment of returns) from daily returns from data going 12 months into the past for all futures. Commodities are then sorted into quintiles and investor goes long quintile containing the commodities with the 20% lowest total skewness and short quintile containing the commodities with the 20% highest total skewness (over a ranking period of 12 months). Resultant portfolio is equally weighted and rebalanced each month.

Hedge for stocks during bear markets

Yes - Based on the source research paper (see Appendix B), strategy has a significantly negative correlation to equity market therefore probably can be used as a hedge/diversification to equity market risk factor during bear markets.

Source Paper

Fernandez-Perez, Frijns, Fuertes, Miffre: Commodities as Lotteries: Skewness and the Returns of Commodity Futures
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2671165
Abstract:
This article studies the relation between skewness and subsequent returns in commodity futures markets. Systematically buying commodities with low skewness and shorting commodities with high skewness generates a significant excess return of 8% a year, which is not merely a compensation for the risks associated with backwardation and contango. Skewness is also found to explain the cross-section of commodity futures returns beyond exposures to the backwardation and contango risk factors previously identified. These results are robust to various alternative specifications and extend the documented importance of skewness in the equity market to the commodity futures markets.

Other Papers

Hypothetical future performance