Fast and Furious: A High-Frequency Analysis of Robinhood Users’ Trading Behavior

ArXiv ID: 2307.11012 “View on arXiv”

Authors: Unknown

Abstract

We analyze Robinhood (RH) investors’ trading reactions to intraday hourly and overnight price changes. Contrasting with recent studies focusing on daily behaviors, we find that RH users strongly favor big losers over big gainers. We also uncover that they react rapidly, typically within an hour, when acquiring stocks that exhibit extreme negative returns. Further analyses suggest greater (lower) attention to overnight (intraday) movements and exacerbated behaviors post-COVID-19 announcement. Moreover, trading attitudes significantly vary 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: Robinhood investors, intraday trading, contrarian strategy, price reactions, retail trading, Equities

Complexity vs Empirical Score

• Math Complexity: 3.0/10
• Empirical Rigor: 8.5/10
• Quadrant: Street Traders
• Why: The paper uses advanced econometric techniques (e.g., regressions on high-frequency data) but focuses on empirical analysis of real-world trading behavior, with heavy data processing and robustness checks, making it highly backtest-ready.

  flowchart TD
    A["Research Goal:<br>Analyze RH Investors' Intraday<br>Trading Reactions"] --> B["Data & Inputs:<br>Robinhood Trading Data +<br>Hourly/Overnight Stock Returns"]
    B --> C["Computational Process:<br>High-Frequency Regression Models"]
    C --> D{"Key Findings"}
    D --> E["Behavioral Preference<br>Strong Buy on Big Losers"]
    D --> F["Rapid Reaction<br>Trade within 1 Hour of Drop"]
    D --> G["Contrarian Strategy<br>Buys Large-Cap Losers"]
    D --> H["Event Sensitivity<br>Heightened Activity Post-COVID"]