A Pond for Small Fish? News and  (Retail) Trading After-Hours

Abstract

We explore after-hours trading (AHT) in the U.S. equity market, focusing on the effect of AHT news releases on market quality. We show that scheduled and positive after-hours firm-specific news catches the attention of retail participants. We use a machine learning algorithm on Robinhood retail popularity to construct a new measure of retail activity during AHT. We identify the buyer-initiated odd-lot trades on the CBOE exchange, which offers a platform (EDGX) with retail priority, as the main predictor of AHT retail activity. The second extension of trading hours on the Robinhood platform provides additional support for retail identification. The introduction of retail priority on the CBOE EDGX platform significantly reduces profits to liquidity provision on earnings news days with high AHT return volatility, suggesting picking-off risk for retail traders.

Keywords: After-hours trading, insider trades, Robinhood, machine learning, retail priority, news

JEL Classification: G10, G12, G14