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Agricultural commodity futures trading based on cross-country rolling quantile return signals

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  • Huayun Jiang
  • Neda Todorova
  • Eduardo Roca
  • Jen-Je Su

Abstract

This paper formulates and examines a new type of bivariate time series trading strategy based on signals generated from cross-country quantiles of return distributions. We conduct rolling quantile trading strategies separately in the U.S. and Chinese futures markets for soybeans, wheat, corn and sugar over very short (daily, intraday and overnight) holding periods. Overall, we find that these practical strategies outperform various benchmarks and there is a large profit potential when trades follow quantile-based signals rather than focusing on the median only. The results highlight the value of cross-country trading strategies and the harnessing of information from different parts of the return distributions which have so far been neglected.

Suggested Citation

  • Huayun Jiang & Neda Todorova & Eduardo Roca & Jen-Je Su, 2019. "Agricultural commodity futures trading based on cross-country rolling quantile return signals," Quantitative Finance, Taylor & Francis Journals, vol. 19(8), pages 1373-1390, August.
    • Handle: RePEc:taf:quantf:v:19:y:2019:i:8:p:1373-1390
    DOI: 10.1080/14697688.2019.1571682
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    Cited by:

    1. Cao, Guangxi & Xie, Wenhao, 2022. "Detrended multiple moving average cross-correlation analysis and its application in the correlation measurement of stock market in Shanghai, Shenzhen, and Hong Kong," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    2. Zheng, Xuyun & Pan, Zheng, 2022. "Responding to import surges: Price transmission from international to local soybean markets," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 584-597.
    3. Elroi Hadad & Davinder Malhotra & Srinivas Nippani, 2024. "Trading commodity ETFs: Price behavior, investment insights, and performance analysis," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(7), pages 1257-1276, July.
    4. Liu, Jiatong & Mao, Weifang & Qiao, Xingzhi, 2023. "Dynamic and asymmetric effects between carbon emission trading, financial uncertainties, and Chinese industry stocks: Evidence from quantile-on-quantile and causality-in-quantiles analysis," The North American Journal of Economics and Finance, Elsevier, vol. 65(C).
    5. Zhang, Xingmin & Zhang, Shuai, 2021. "Optimal time-varying tail risk network with a rolling window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).

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