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Do Individual Day Traders Make Money? Evidence from Taiwan Brad Barber Yi-Tsung Lee Yu-Jane Liu Terrance Odean

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Presentation on theme: "Do Individual Day Traders Make Money? Evidence from Taiwan Brad Barber Yi-Tsung Lee Yu-Jane Liu Terrance Odean"— Presentation transcript:

1 Do Individual Day Traders Make Money? Evidence from Taiwan Brad Barber Yi-Tsung Lee Yu-Jane Liu Terrance Odean

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5 Research Questions What is the performance profile of Day Traders? (1) Return and Gross Profit (2) Net Profit (3) Cross-sectional Performance What is the order type underlying their trade? Does performance influence sequent day trading?

6 Why Day Trading? Regulatory Scrutiny –Senate Investigations (9/1999) –SEC, NASD, NYSE –Result: suitability rules and “crackdown” on deceptive advertising Two Important Questions –Do day traders systematically lose money? –Does day trading destabilize markets?

7 Prior Research Harris and Schultz (1998) –One broker; 20,000 trades; 3 weeks –Traders earn small average profit Garvey and Murphy (2001) –One broker; 15 day traders; 96,000 trades; 3 mths –Make money by providing liquidity inside dealer quotes Jordan and Diltz (2003) –One broker; 324 traders; 12 mths –60% lose money Linnainmaa (2003) –Finnish Data –Tend to lose money, but does not analyze persistence

8 Individual Investor Performance Large U.S. Brokerage Data –Odean (1999) –Barber and Odean (2000, 2001) Finnish Data –Grinblatt and Keloharju (2000) Taiwan Data –Barber, Lee, Liu, and Odean (2004) Others –Schlarbaum et al. (1978) –Coval, Hirshleifer, and Shumway (2003)

9 Taiwan Stock Exchange World’s 12 th largest financial market. 6.8 million (31 percent) of Taiwan’s population of 22.2 had opened a brokerage account as of end of Electronic limit order market. Daily price change limits of 7 percent. Cap of percent on commissions. Transaction Tax – 0.3 percent on Sales No capital gains tax.

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14 Data All trades on TSE: 1995 to 1999 Identification of Investors –Institutions Corporations Dealers Foreigners Mutual Funds –Individuals

15 Growth of $1 invested in Taiwan Index on December 31, 1994

16 The Data Taiwan Stock Exchange

17 Trader Types Individual Investors Corporate Investors Foreign Investors Dealers Mutual Funds No. of Traders 3,944,93224,3581, % of All Trades (by value) Ave. Size of Buy (TW $) 190,256384,771353,560426,463433,411 Ave Size of Sell (TW $) 190,995384,454314,805416,701365,017

18 Event-Time Results Cumulative Market-Adjusted Returns

19 Mean Daily Profits Net of Transaction Costs InstitutionsIndividuals Gross Profits178.0(178.0) Commissions(25.6)(216.9) Transaction Tax(27.0)(228.4) Net Profits125.4(623.3)

20 Economic Significance Individual Losses –3.5% annually Average Individual Trader –US$7,545 loss over five years In total amount of individual losses, 1.5% of Total Personal Income in Taiwan

21 Economic Significance Institutional Gains –1.0% annually –Before management fees (information costs) Institutions earn $NT 35 bil. –Assume inv’t prof. are paid $NT 3.2 mil. / year  Supports an industry of 11,000 professionals

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23 ALL TRADEDAY TRADE Day Trade % of All Trade Investor Type Value ($NT Mil) % of All Trd Value ($NT Mil) % of Day Trd All Traders170, , All Individ.152, , All Inst.17, Corporations7, Dealers2, Foreigners3, Mutual Funds4, Table 1: Mean Daily Value of Trade

24 Figure 1: Trading Volume in Taiwan

25 Performance Measurement Assumptions 10 bp one-way commission 3 bp transaction tax on sales Perfect accounting for day trades Non-day trades are evaluated using closing prices –Implicit Assumption: no gains (or losses) beyond day of trade –Robustness: Evaluation periods up to 10 days yield qualitatively similar results

26 Sample Trader/Day Buy A ($10) Sell A ($12) Close A ($11) B($5) C($8) Buy B ($4) Short C ($9) Buy A: (11-10) = 1 Sell A (12-11) = 1 Buy B (5-4) = 1 Sell C (9-8) = 1 Gross Profit: $4 Trans. Costs: Commissions $0.35 ($25 x 0.1%) Sales Tax $0.66 ($21 x 0.3%)

27 Performance Measurement Aggregate Trades within Partition - the value of day trade summed over past six months - mean daily profit scaled by its std. during past six months Calculate intraday trading profits as:

28 Performance Measurement Compare returns of stocks bought to those sold:

29 Research Questions Based on past trading activity What is the performance profile of Day Traders? (1) Return and Gross Profit (2) Net Profit (3) Cross-sectional Performance What is the order type underlying their trade? Does performance influence sequent day trading?

30 Identifying Day Traders A. Partitioned by Past Day Trading Activity Sum Day Trades over six month for each investor Partition All Investors based on day trading Jan Feb Mar Apr May June July Aug Analyze performance of All Trades for Partition

31 Table 2: Descriptive Statistics for Day Trader Partitions ALL TRADEDAY TRADE Partition Range Value ($NT Mil) % of All Trade Value ($NT Mil) % of Day Trade Day Trade % of All Trade Mean No. of Acc. Mean Dly Volume (per Acc.) (000) (600m, ∞)11, , ,280 (240m, 600m)12, , ,2245,598 (90m, 240m)18, , ,3032,868 (15m, 90m)36, , ,9441,163 (1.5m,15m)32, , , (0.3m, 15m)10, , , (0, 0.3m)39, , , Panel A: Individual Investors Partitioned by Past Day Trading Activity

32 Accounts sorted by Past Day Trading Activity Intraday Buy Return less Intraday Sell Return

33 Accounts sorted by Past Day Trading Activity Mean Daily Profits per Account

34 Table 3: Gross Performance of Day Traders Partition Range Buy less Sell Return (%)t-stat Mean Daily Gross Profit ($NT Mil) t-stat % Days with Profit (600m, ∞) * *90.7* (240m, 600m) * *80.4* (90m, 240m) * *67.2* (15m, 90m) * *42.8* (1.5m,15m) * *21.2* (0.3m, 15m) * *20.8* (0, 0.3m) * *21.2* Panel A: Individual Investors Partitioned by Past Day Trading Activity

35 Table 4: Net Performance of Day Traders Partition Range Mn Dly Net Pft ($NT Mil) t-stat Percentage of Days with Profit Number of Accounts Mn Dly Net Pft (Loss) per Account ($NT) (600m, ∞) *28.3*862-8,443 (240m, 600m) *4.0*2,224-9,707 (90m, 240m) *0.7*6,303-6,351 (15m, 90m) *0.2*30,944-3,033 (1.5m,15m) *0.0*87,833-1,073 (0.3m, 15m) *0.0*78, (0, 0.3m) *0.0*719, Panel A: Individual Investors Partitioned by Past Day Trading Activity

36 Cross-Sectional Analysis Jan-Jun 95 Jul-Dec 95 Jan-Jun 96 Jul-Dec 96 Group Traders Estimate Profits (per trader) Group Traders Estimate Profits (per trader) Group Traders Estimate Profits (per trader) Evaluate Performance of Investors in 9 Semiannual Periods Calculate Mean/Median across Investors

37 Table 6: Cross-Sectional Performance of Day Traders Partition Range Number of Investors % of Investors with Profits Mean Profit per Investor over 6 mths ($NT) Median Profit per Investor over 6 mths ($NT) (600m, ∞) *-360,138*-282,600* (240m, 600m)2, *-777,121*-481,127* (90m, 240m)6, *-574,011*-319,939* (15m, 90m)32, *-302,449*-142,474* (1.5m,15m)93, *-117,572*-46,146* (0.3m, 15m)87, *-45,063*-15,597*

38 Research Questions Based on past daily profit scaled What is the performance profile of Day Traders? (1) Return and Gross Profit (2) Net Profit (3) Cross-sectional Performance What is the order type underlying their trade? Does performance influence sequent day trading?

39 Identifying Day Traders B. Partitioned by Standardized Past Profits Calculate Daily Profits for each Investor over six month period Calculate mean daily profits scaled by standard deviation of profits (deals with scale issues) Partition investors with a minimum of 35 days of trading activity Jan Feb Mar Apr May June July Aug Analyze performance of All Trades for Partition

40 Table 2: Descriptive Statistics for Day Trader Partitions ALL TRADEDAY TRADE Partition Range Value ($NT Mil) % of All Trade Value ($NT Mil) % of Day Trade Day Trade % of All Trade Mean No. of Acc. Mean Dly Volume (per Acc.) (000) (.2, ∞) 2, , ,786 (.1,.2) 3, , ,0623,490 (0,.1) 6, , ,0272,292 (-.2, 0) 22, , ,0691,337 (-.4, -.2) 21, , , (-∞, -.4) 8, , ,6381,085 No Rank 95, , , Panel B: Individual Investors Partitioned by Standardized Past Profits

41 Accounts sorted by Past Trading Profits Intraday Buy Return less Intraday Sell Return

42 Accounts sorted by Past Trading Profits Mean Daily Profits per Account

43 Table 3: Gross Performance of Day Traders Partition Range Buy less Sell Return (%)t-stat Mean Daily Gross Profit ($NT Mil) t-stat % Days with Profit (.2, ∞) * *97.0* (.1,.2) * *94.9* (0,.1) * *92.1* (-.2, 0) * *89.3* (-.4, -.2) * *21.1* (-∞, -.4) * *18.0* Panel B: Individual Investors Partitioned by Standardized Past Profits

44 Table 4: Net Performance of Day Traders Partition Range Mean Daily Net Profit ($NT Mil) t-stat Percentage of Days with Profit Number of Accounts Mn Dly Net Profit (Loss) per Account ($NT) (.2, ∞) *71.1*3937,532 (.1,.2) *49.51,0621,445 (0,.1) *30.3*3,027-1,112 (-.2, 0) *2.6*17,069-2,396 (-.4,-.2) *0.0*22,158-3,100 (-∞, -.4) *0.2*7,638-4,342 Panel B: Individual Investors Partitioned by Standardized Past Profits

45 Table 6: Cross-Sectional Performance of Day Traders (Profit Partition) Partition Range Number of Investors % of Investors with Profits Mean Profit per Investor over 6 mths ($NT) Median Profit per Investor over 6 mths ($NT) (.2, ∞) *1,137,230*125,761* (.1,.2)1, *299,124*-8,377 (0,.1)3, *-41,853*-36,783* (-.2, 0)17, *-223,684*-73,795* (-.4,-.2)22,6646.6*-308,131*-110,860* (-∞, -.4)7,9233.1*-434,195*-166,370* Panel B: Individual Investors Partitioned by Standardized Past Profits

46 Research Questions What is the performance profile of Day Traders? (1) Return and Gross Profit (2) Net Profit (3) Cross-sectional Performance What is the order type underlying their trade? Does performance influence sequent day trading?

47 Identifying Aggressive and Passive Trades Price Buy Orders Sell Orders Shares Cleared ask price bid price Buy Orders > Sell Orders < 9.90

48 Table 5: Liquidity Providers? Percentage of Trades Emanating from Orders Classified as: Partition Range PassiveAggressiveIndeterminate All Individual Investors (600m, ∞) (240m, 600m) (90m, 240m) (15m, 90m) (1.5m,15m) (0.3m, 15m) (0, 0.3m) Panel A: Individual Investors Partitioned by Past Day Trading Activity

49 Table 5: Liquidity Providers? Percentage of Trades Emanating from Orders Classified as: Partition Range PassiveAggressiveIndeterminate All Individual Investors (.2, ∞) (.1,.2) (0,.1) (-.2, 0) (-.4,-.2) (-∞, -.4) Panel B: Individual Investors Partitioned by Standardized Past Profits

50 Research Questions What is the performance profile of Day Traders? (1) Return and Gross Profit (2) Net Profit (3) Cross-sectional Performance What is the order type underlying their trade? Does performance influence sequent day trading?

51 Table 7: Change in Day Trading and Past Performance

52 “Light” Day Traders

53 “Heavy” Day Traders

54 Discussion Why do Day Traders Lose? Liquidity Needs? –Day trading exceeds 20% of volume –Annual turnover is greater than 300% Entertainment Overconfidence

55 Conclusion Performance of Day Traders The average day trader –Makes gross profits –Loses money after costs –Heavy day traders lose money after costs 8 of 10 day traders lose money Some day traders consistently profit


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