Dynamic efficiency of China’s commodity futures market through the lens of high frequency data

He Chengying, Huang Ke, Wen Zhang and Huang Qingcheng
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He Chengying: Sino-UK Blockchain Industry Research Institute, Guangxi University, Nanning 530004, P. R. China
Huang Ke: Sino-UK Blockchain Industry Research Institute, Guangxi University, Nanning 530004, P. R. China
Wen Zhang: Sino-UK Blockchain Industry Research Institute, Guangxi University, Nanning 530004, P. R. China
Huang Qingcheng: Sino-UK Blockchain Industry Research Institute, Guangxi University, Nanning 530004, P. R. China

International Journal of Financial Engineering (IJFE), 2022, vol. 09, issue 01, 1-17

Abstract: In this paper, we use the permutation entropy algorithm to derive the static and dynamic permutation entropy of commodity futures, and to evaluate the effectiveness of main products in China’s commodity futures market. The intraday data of six varieties belonging to six categories in China’s commodity futures market are taken as samples. We find the following: (1) The return distribution of the main varieties shows high peaks, fat tails and asymmetry, and follows the biased random walk distribution characteristics; (2) The permutation entropy of all varieties decreases significantly in the same time window, during which the price volatility of major commodity markets rises. And the time window coincides with the impact time of COVID-19 epidemic; (3) By comparing the distribution of permutation entropy of main varieties in different stages of event shock, we found that the mean value of permutation entropy decreases significantly during the process of event shock, and the price fluctuates greatly. Therefore, the significant decrease of permutation entropy is a valuable warning signal for regulators and investors.

Keywords: China commodity futures; dynamic permutation entropy; rolling window; nonlinear adaptive multiscale decomposition (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S2424786321410127

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