The cross section of Chinese commodity futures return
The cross section of Chinese commodity futures return
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DOI：
10.1016/j.jmse.2021.03.001
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发表时间：
2021-03
期刊：
影响因子：
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通讯作者：
Bin Li;Cheng Sun;Yang Zhou
中科院分区：
文献类型：
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作者：
Bin Li;Cheng Sun;Yang Zhou
本文使用包含 13 个单独因素的大型面板研究了中国商品期货预期回报的横截面。我们发现 13 个单独因素中有 6 个会产生积极且显着的回报。为了汇总这些因素之间的信息，我们不仅应用了传统的 Fama-MacBeth 回归（FM），还应用了一系列替代方法，包括预测组合方法（FC）、主成分分析（PCA）、主成分回归（PCR）和偏最小二乘法（PLS）。事实证明，PLS 在预测中国预期期货收益横截面方面优于其他方法。与每种单一方法相比，5 种方法的等权组合可产生更高的年化回报和更低的标准差。对因子重要性的考察表明，偏度（SKEW）因子在预测中国市场预期期货收益方面比其他因子更重要。
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 factors, we apply not only the traditional Fama-MacBeth regression (FM), but also a set of alternative methods, including the forecast combination method (FC), principal component 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.