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Attention-Induced Trading and Returns: Evidence from Robinhood Users

Journal: Journal of Finance

Date: 20221201

Author: Barber, Brad M.; Huang, Xing; Odean, Terrance; Schwarz, Christopher

Abstract:
We study the influence of financial innovation by fintech brokerages on individual investors' trading and stock prices. Using data from Robinhood, we find that Robinhood investors engage in more attention-induced trading than other retail investors. For example, Robinhood outages disproportionately reduce trading in high-attention stocks. While this evidence is consistent with Robinhood attracting relatively inexperienced investors, we show that it is also driven in part by the app's unique features. Consistent with models of attention-induced trading, intense buying by Robinhood users forecasts negative returns. Average 20-day abnormal returns are -4.7% for the top stocks purchased each day.

Link: Google Scholar

Key Findings

Concentrated Trading Activity

Robinhood users show more concentrated buying behavior than other retail investors, with 35% of net buying concentrated in 10 stocks versus 24% for general retail investors

Negative Returns After Herding

Stocks experiencing intense buying by Robinhood users ("herding events") show average 20-day abnormal returns of -4.7%, with more extreme herding events showing returns up to -19.6%

App Interface Impact

The Robinhood app's simplified interface and "Top Movers" list influences trading behavior, leading users to trade both extreme gainers and losers unlike other retail investors

Trading Concentration Comparison

  • Robinhood users concentrate 35% of net buying in top 10 stocks
  • General retail investors concentrate 24% of net buying in top 10 stocks
  • Shows higher herding tendency among Robinhood users

Returns Following Herding Events

  • 20-day abnormal returns average -4.7% for herding events
  • Returns become more negative as herding intensity increases
  • Most extreme herding events (750% user increase) show -19.6% returns

Impact of Market Cap on Returns

  • Small-cap stocks (<$1B) show -3.8% to -4.3% returns after herding
  • Large-cap stocks (>$1B) show no significant return pattern
  • Effect is stronger during COVID-19 period (after March 2020)

Contribution and Implications

  • First study to show how fintech app design influences retail trading behavior
  • Demonstrates that simplified interfaces can lead to concentrated trading and losses
  • Highlights need for balanced information display in trading applications
  • Questions effectiveness of "gamification" in investment platforms

Data Sources

  • Trading concentration data from Table III comparing Robinhood and TAQ retail trades
  • Returns analysis based on Table VIII showing event-time abnormal returns
  • Market cap analysis derived from Table XII showing subsample return patterns