IEEE Access (Jan 2018)

Sparse Trading, Information Transmission and Futures Prices Recovery (August 2018)

  • Zheng Zunxin,
  • Wang Qi,
  • Zhu Fumin

DOI
https://doi.org/10.1109/ACCESS.2018.2867155
Journal volume & issue
Vol. 6
pp. 50278 – 50289

Abstract

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This paper proposes a sparse trading model of futures prices. The model considers that nearby futures contract with liquidity plays an important role in the price recovery, and allows that far futures contract with sparse trading uses the price of nearby futures contract as a source of information. Also, it is shown whether and how liquidity may well be an influential factor for futures prices in Chinese commodity futures markets. Empirical results show strong evidence for lead-lag information transmission for fuel oil, nature rubber, and soybean, which implies sparse trading effect on futures prices.

Keywords