首页|Findings in the Area of Machine Learning Reported from Shanghai Jiao Tong University (Commodity Factor Investing Via Machine Learning)
Findings in the Area of Machine Learning Reported from Shanghai Jiao Tong University (Commodity Factor Investing Via Machine Learning)
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NETL
NSTL
Elsevier
Current study results on Machine Learning have been published. According to news reporting originating from Shanghai, People’s Republic of China, by NewsRx correspondents, research stated, “We investigate the factor investing in Chinese commodities markets following two steps. The first step is to find profitable characteristics.” Financial support for this research came from National Natural Science Foundation of China (NSFC). Our news editors obtained a quote from the research from Shanghai Jiao Tong University, “We find that some technical characteristics can produce a comparable out-of-sample performance to the fundamental characteristics. The second step is to integrate various commodity characteristics to generate a composite signal. We apply the naive equal-weighted model, three linear models and four tree-ensemble nonlinear models for style integration. The empirical results show that the four nonlinear machine learning integration models produce better out-of-sample performance than the linear models.”
ShanghaiPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningShanghai Jiao Tong University
NETL
NSTL
Elsevier
