Algorithmic Trading, Liquidity, and Price Discovery: An Intraday Analysis of the SPI 200 Futures

We study the intraday price impact of algorithmic trading (AT) on futures markets. We find that AT exhibits a strong reverse U-shape intraday pattern, and greater AT activity is related to lower effective spreads, higher realized spreads and lower adverse selection risk, which suggests that algorithmic traders strategically enter the market when transaction costs and information asymmetry are lower. AT is associated with an increase in transaction costs in the subsequent intraday period mainly through an increase in the adverse selection risk, and is positively related to both public and private information. Our results strongly suggest that algorithmic traders are informed and contribute to liquidity and price discovery on the futures markets.