Exploring the relationship between Chinese crude oil futures market efficiency and market micro characteristics

Abstract

This paper uses daily frequency data spanning from March 26, 2018 to February 3, 2023, and combines the exponential generalized autoregressive conditional heteroskedasticity in mean (EGARCH-M) model with the time-varying parameters state-space (TVPSS) model to dynamically test the efficiency of the Chinese crude oil futures market (CCOFM). Additionally, the paper examines the relationship between market efficiency and market micro characteristics such as market depth, market liquidity, noise trading, speculation rate, and information asymmetry. The results show that the CCOFM exhibited weak-form efficiency in June 2020, which lasted until the end of February 2022, and after that, the efficiency showed a poor development trend. Analyzed from the macro level, the Market Maker System and Trader Suitability System have a positive effect on market efficiency, while the Russian-Ukrainian conflict has a negative effect on market efficiency. Analyzed from the micro level, market depth and information asymmetry have a positive effect on market efficiency, while the speculation rate has a negative effect on market efficiency, and noise trading and market liquidity have no significant effect on market efficiency. Market efficiency has a positive effect on market depth and a negative effect on speculation rate. Market liquidity and noise trading have a positive effect on speculation rate, while both information asymmetry and market liquidity have a negative effect on noise trading. In addition, speculation rate has a weak negative effect on information asymmetry, and market depth and speculation rate have a weak positive effect on market liquidity. This study provides theoretical support and decision-making foundation for the development of CCOFM by dynamically exploring the relationship between CCOFM efficiency and micro characteristics.