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The cross section of Chinese commodity futures return

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This paper investigates the cross-section of expected commodity futures returns in China using a large panel of 13 individual factors.We find that 6 out of 13 individual factors produce positive and significant returns.To aggregate the information among these fac-tors,we apply not only the traditional Fama-MacBeth regression (FM),but also a set of alternative methods,including the forecast combination method (FC),principal compo-nent analysis (PCA),principle component regression (PCR) and partial least squares (PLS).It turns out that PLS outperform other methods in forecasting the cross-section of Chinese expected futures returns.The equally weighted combination of 5 methods produces an even higher annualized return and lower standard deviation compared to each single method.The investigation of factor importance reveals that the skewness (SKEW) factor is more important than other factors in predicting expected futures returns in Chinese markets.

Commodity futures factorsCross-section of expected futures returnsPartial least squares

Bin Li、Cheng Sun、Yang Zhou

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Economics and Management School,Wuhan University,China

McDonough School of Business,Georgetown University,USA

This work was partially done when Bin Li was a visiting scholar at the McDonough School of Business,Georgetown UniversityThis work was supported by the National Natural Science Foundation of ChinaThis work was supported by the National Natural Science Foundation of ChinaThis work was supported by the National Natural Science Foundation of ChinaMajor Program of the National Social Science Foundation of ChinaMOE (Ministry of Education in China)Project of Humanities and Social SciencesFundamental Research Funds for the Central UniversitiesWe thank conference and seminar participants at GCAFC 2019,ICFOD 2019,Wuhan University,etc

71971164916462067170311418ZDA09218YJCZH0722020AI010

2021

管理科学学报(英文)

管理科学学报(英文)

ISSN：2096-2320
年,卷(期)：2021.6(2)
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