Do Noise Traders Move Markets?

1. Do Noise Traders Move Markets? Brad Barber Terrance Odean Ning Zhu

2. Do Noise Traders Move Markets? • Small trades are proxy for individual investors trades. • Individual investors trading is correlated: • Across stocks • Across months • Individual investor trading forecasts returns: • Short-term outperformance • Medium and long-term underperformance www.swingtum.com/institute/IWIF

3. Theory • Informed traders are constrained (limits of arbitrage): • Costs • Short Sale Constraints • Risk aversion • Noise traders are emotional. • Noise trading is correlated. • Noise trading moves prices from fundamental value. • Informed trading (eventually) pushes prices back to fundamental value. Shleifer & Summers (1990) De Long, Shleifer, Summers, & Waldman (1990, 1991) Shleifer, Summers, & Vishny (1991) www.swingtum.com/institute/IWIF

4. Informed traders are constrained. • Closed-end funds Pontiff (1996) • Short sale constraints Lamont & Jones (2002), Cohen, Diether, Malloy (2006) Bris, Woetzmann, and Zhu (2006) • S & P 500 additions Harris & Gurel (1986), Shleifer (1986) Wurgler and Zhravskaya (2002) www.swingtum.com/institute/IWIF

5. 2. Noise traders are emotional. • Overconfidence Odean (1999) Barber & Odean (2000, 2001) Nicolosi, Peng, and Zhu (2006) • Disposition effect Shefrin & Statman (1985) Odean (1998) , Dhar and Zhu (2006) Grinblatt and Keloharju (2001) • Representativeness DeBondt (1993) DeBondt and Thaler (1997) • Limited attention Barber & Odean (2005), Hirshleifer, Hou & Teo (2005) Huberman (2002), Zhu (2005), Seasholes and Zhu (2006) www.swingtum.com/institute/IWIF

6. 3. Noise trading is correlated. • U.S. Brokerage Data (Barber, Odean, and Zhu, 2004) • U.S. discount broker, 1991-96 • U.S. full-service broker, 1997-99 • Australian investors, 1991-2002, (Jackson, 2003) • All U.S. small trades 1983-2000 (This paper) www.swingtum.com/institute/IWIF

7. Primary Contribution of Paper. • Informed traders are constrained (limits of arbitrage): • Costs • Short Sale Constraints • Risk aversion • Noise traders are emotional. • Noise trading is correlated. • Noise trading moves prices from fundamental value. • Informed trading (eventually) pushes prices back to fundamental value. • Shleifer & Summers (1990) • De Long, Shleifer, Summers, & Waldman (1990, 1991) • Shleifer, Summers, & Vishny (1991) www.swingtum.com/institute/IWIF

8. Data • Tick-by-tick transaction data: 1983 to 2000 • Institute for the Study of Securities Markets (ISSM) NYES & ASE 1983-1992; Nasdaq 1987-1992. • Trade and Quote (TAQ) NYSE, ASE, & Nasdaq, 1992-2000 • Decimalization in January 2001 • Dramatic shift in the distribution of trade size • Small trade becomes poor proxy for individual investor trades www.swingtum.com/institute/IWIF

9. Number of Small Trades and Large Trades between 1/2000 and 12/2001 www.swingtum.com/institute/IWIF

10. Signing trades as buyer or seller initiated Trade Executes @ 10 1/8 ASK: 10 1/8 Buyer initiated Midpoint: 10 1/16 Trade Executes @ 10 Seller initiated BID: 10 www.swingtum.com/institute/IWIF

11. Signing trades Details • Quote rule: buyer initiated if above midpoint of quotes. • Tick rule: buyer initiated if above last executed trade. • NYSE and ASE – applied to trades at midpoint • Nasdaq – applied to trades within quotes Ellis, Michaely, and O’Hara (2000) • Ignore NYSE and ASE opening trades. Lee and Ready (1991) www.swingtum.com/institute/IWIF

12. Trade size as proxy for investor type • Lee & Radhakrishna (2000) • T ≤ $5,000 (Small trades, i.e., individual investors) • $5,000 < T ≤ $10,000 • $10,000 < T ≤ $20,000 • $20,000 < T ≤ $50,000 • $50,000 < T (Large trades, i.e., institutional investors) • 1991 dollars indexed to CPI www.swingtum.com/institute/IWIF

13. Measuring Trade Imbalance • Calculate ratio by trade value and trade number. • Calculate separate imbalance measure for each of five trade size quintiles. • Ignore stocks with less than 10 signed trades. www.swingtum.com/institute/IWIF

14. Are small signed trades a good proxy for individual investor trades? Calculate monthly proportion buys for: • U.S. Discount Broker Data • 1991 to 1996 • 78,000 investors • U.S. Full-Service Broker Data • 1997 to 1999 • 650,000 investors • Transaction Level Data – Five Trade Size Bins In each month, calculate correlation across datasets Average Correlations across months www.swingtum.com/institute/IWIF

15. Small trades as proxy for individual investors Mean Monthly Correlation in the Proportion of Trades that are Buyer Initiated across Datasets www.swingtum.com/institute/IWIF

16. Correlation Matrix in Proportion of Trades that are Buyer Initiated for Five Trade Size Bins www.swingtum.com/institute/IWIF

17. Are the trades of individual investors correlated over time? • Percentage Spread between Deciles 1 and 10 • Week Small Trades Large Trades 0 58.1 55.9 1 23.0 8.1 3 16.9 4.7 6 13.7 3.4 12 10.4 2.8 www.swingtum.com/institute/IWIF

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20. Do Noise Traders Move Prices? • Calculate Annual Proportion Buys • December 1983 to December 2000 • Separately for Small Trades and Large Trades • Sort Stocks into Quintiles • Construct Portfolios based on Quintile Sorts • Calculate Monthly Portfolio Returns in year following formation www.swingtum.com/institute/IWIF

21. Descriptive Statistics www.swingtum.com/institute/IWIF

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23. Abnormal Returns • Market-Adjusted Returns • Four-Factor Alphas • Market • Size (SMB) • Value (HML) • Momentum (UMD) www.swingtum.com/institute/IWIF

24. Mean Monthly Percentage Abnormal Returns Portfolios formed on the basis of Annual Proportion of Buyer-Initiated Trades: 1984 to 2001 www.swingtum.com/institute/IWIF

25. Monthly Percentage Abnormal Returns for Portfolios formed from Five-by-Five Partition on Proportion Buyer-Initiated Trades based on Small Trades (columns) and Large Trades (Rows) Equally-Weighted Portfolios www.swingtum.com/institute/IWIF

26. Monthly Percentage Abnormal Returns by Firm Size for Value-Weighted Portfolios formed on the basis of Proportion Buyer-Initiated Trades using Small and Large Trades www.swingtum.com/institute/IWIF

27. Monthly Percentage Abnormal Returns by Small Trade Turnover for Value-Weighted Portfolios formed on the basis of Proportion Buyer-Initiated Trades using Small and Large Trades www.swingtum.com/institute/IWIF

28. Mean Monthly Percentage Abnormal Returns for Portfolios formed on the basis of Weekly Proportion of Buyer-Initiated Trades: 1984 to 2001 www.swingtum.com/institute/IWIF

29. Cross-Sectional Regressions of Weekly Returns • Dependent Variable: Weekly Return • Independent Variables: • Trading Variable • Weekly Lags of Proportion Buys based on Small Trades (through one year) • Control Variables: • Size • Book-to-Market • Four Lags of Weekly Returns (Short-term Reversals) • Return from week t-52 to t-5 (Momentum) www.swingtum.com/institute/IWIF

30. Fama-MacBeth Regressions Mean coefficient estimates from weekly cross-sectional regressions of return on lagged small trade imbalance www.swingtum.com/institute/IWIF

31. Do Noise Traders Move Markets? • Push prices in short-term… • Weekly Horizon • Stocks bought outperform stocks sold in subsequent week • Leading to poor long-run returns • Annual Horizon • Stocks bought underperform stocks sold in subsequent year www.swingtum.com/institute/IWIF

32. Implications to Asian Markets • Greater individual presence • Electronic trading system • Relatively less efficient price discovery • Greater profitability from noise traders?? www.swingtum.com/institute/IWIF