Research on Algorithmic Trading and Its Role in Pricing Efficiency in Chinese Stock Market

Abstract

This paper uses the A-share stock data in 2021 as a sample to study the impact of algo-rithmic trading activities on pricing efficiency through empirical analysis. Combining with the current market transaction structure and institutional characteristics in China, this study uses the proportion of small transaction volume STR as a proxy variable to measure the in-tensity of algorithmic trading activities in China. Empirical results show that algorithmic trading can effectively improve the pricing efficiency of Chinese stock market. In addition, an important way for algorithmic trading to improve pricing efficiency is to reduce stock market volatility and reduce investor heterogeneity. Through extended analysis, the find-ings demonstrate that algorithmic trading has a differential impact on the pricing efficien-cy of different stocks, with the highest degree of improvement in pricing efficiency for stocks with high market prices; at the same time, algorithmic trading can play a better role under the condition of sufficient market liquidity.