Examining High-Frequency Patterns in Robinhood Users' Trading Behavior

Abstract

We examine Robinhood (RH) investors' intraday and overnight trading behaviors in response to high-frequency price movements and identify three patterns: (i) a strong reaction to extreme price movements, (ii) an asymmetric attitude toward extreme movers with a preference for big losers over big gainers, and (iii) a rapid response to negative price movements. Contrasting these high-frequency behaviors with those found in the previous literature based on daily data, we reveal that the asymmetry is underestimated with daily data. We also uncover new insights on reaction speed, measured in hours, which cannot be assessed at the daily level. The relevance of the high-frequency analysis aligns with the ultra-connected profile that characterizes most of the RH investors community. Further analyses suggest greater (lower) attention to overnight (intraday) movements and exacerbated behaviors during the COVID-19 pandemic. Moreover, these trading behaviors vary significantly across firm size and industry, with a more contrarian strategy towards larger-cap firms and a heightened activity on energy and consumer discretionary stocks.

Keywords: Attention-Induced Trading, Robinhood, Retail Investors, High-Frequency Data, Reaction Speed, FinTech JEL: G11, G14, G40, G41, G53

JEL Classification: G11, G14, G40, G41, G53