We believe both theory and empirical evidence provide strong support for the view that better informed (institutional) investors will gain from trade, while less informed (individual) investors will lose. In Taiwan, institutions earn gross daily profits of $NT 178 million (roughly $US 6 million), while individuals lose the same amount.
The U.S. equity market is the largest and most developed market in the world.
Consequently, it is useful to compare and contrast the Taiwan and U.S. markets.
In extrapolating our results to other markets such as the U.S., we should bear in mind that the per trade losses suffered by Taiwanese individual investors may be less than the losses of individual investors in markets dominated by institutional investors.
Taiwanese individuals—who account for 89.5% of trading volume—are far more likely to trade with other individuals, as opposed to institutions, than are individuals in countries such as the U.S. Thus, on a per trade basis, Taiwanese individuals are less exposed than U.S. individual investors to asymmetrical informational advantages held by institutional investors. This may be why Taiwanese individuals suffer lower gross trading losses per trade than those documented for U.S. individuals. In Table 4, we report that, over a horizon of 140 trading days, stocks bought by Taiwanese individuals underperform those sold by 4 basis points per month. Similar calculations for U.S.
individuals indicate an underperformance of 20 basis points or more per month (Odean (1999), Barber and Odean (2001)).
Can the prevalence of day trading in Taiwan explain the institutional gains and individual losses that we document? Day trading in Taiwan represents more than 20 percent of total trading volume. Though precise data on day trading in the U.S. is sparse,
estimates of total volume that can be traced to day trading in the U.S. range from 15 to 30 percent.20 Thus, the high incidence of day trading does not appear to be unique to Taiwan.
In addition, Barber, Lee, Liu, and Odean (2004) document that virtually all day trading in Taiwan can be traced to individuals investors. In aggregate day traders earn gross profits (though these profits are not sufficient to cover transaction costs). Thus, the gross losses that we document for all individuals cannot be traced to the activity of individual day traders.
Can the high turnover rates in Taiwan explain the institutional gains and individual losses? Annual turnover in Taiwan during our sample period averaged almost 300 percent; in contrast, turnover in the U.S. during the same period averaged 69 percent.
Individual investors in Taiwan may trade so actively because they find trading more enjoyable than their American counterparts and thus willingly incur large losses for entertainment or they may trade more actively than U.S. investors because they are more overconfident.21 Since Taiwanese individual investors trade so actively—whether for entertainment or because of overconfidence—institutional investors could be earning their profits simply by supplying liquidity—e.g., serving as market-makers—to these overly aggressive investors. If so, we would expect institutional profits to be generated primarily by passive trades and realized at short horizons. While we do document that institutional investors earn short term profits by supplying liquidity to individual investors, approximately half of their profits are from aggressive trades and accrue at horizons of up to six months. This implies that these institutional investors are profiting from their information, not simply from their willingness to supply liquidity. Such an information advantage would be profitable even in the US where individuals are less
20 Britt Tunick, Day Traders Working Hard to Influence How the Profession is to be Defined, SEC.WEEK, May 24, 1999; Day Trading and Beyond: A New Year, An Updated View, Bear Stearngs, January 2001;
David Tabok, Intraday Trading Rate in Shareholder Class Actions, Securities and Finance Insights, June 2002, NERA Economic Consulting.
21 Several studies document overconfidence tends to be greater in some Asian countries (e.g., China) than other cultures (e.g., U.S. and Japan). See, for example, Yates et al. (1998) and Lee et al. (1995).
exuberant traders, However, it is possible that the exuberant trading of Taiwanese individual investors create mispricings that are subsequently exploited by institutions.
Can the regulatory environment in Taiwan explain the gross institutional gains and gross individual losses? We do not believe this is the case for two reasons. First, business leaders and analysts do not perceive Taiwan as unusually corrupt. Transparency International constructs an annual corruption index for over 100 countries based on surveys of business leaders and risk analysts. In the 1999 survey, Taiwan ranked as the 28th least corrupt country – a rating similar to countries with larger stock markets: U.S.
(18th), France (22nd), Spain (22nd), Japan (25th), and Italy (38th).22 Second, the financial reporting requirements and insider trading laws in Taiwan are substantively similar to those in the U.S.
During our sample period, two TSE stocks had level III American Depository Receipts (ADRs) trading in the U.S.: Micronix and Taiwan Semiconductors. The Micronix ADR began trading in the U.S. on May 9, 1996, while the Taiwan Semiconductor ADR began trading on October 8, 1997. This fact provides us with some ability to analyze the effect of the regulatory environment more carefully for two reasons.
First, level III ADRs are required to meet the full registration and reporting requirements of the U.S. SEC's Exchange Act. Second, the presence of an ADR provides a near perfect substitute for the TSE listed stock facilitating arbitrage. In auxiliary analyses, we calculate the daily trading profits for institutions and individuals for these two stocks.
Similar to our overall results, institutions gain, while individuals lose when trading these stocks after the introduction of the ADR. The post-ADR trades in these two stocks account for 9.7 percent of all institutional gains (and individual losses), but only four percent of total trading volume. Thus, the trades in these two stocks, which are very liquid, contain a close substitute in the U.S., and are subject to stringent SEC reporting requirements, are more profitable than other trades. This evidence indicates the unique features of the regulatory environment in Taiwan cannot explain our results.
22 Khwaja and Mian (2003) argue brokers in Pakistan are able to earn high returns by using manipulative trading practices. Pakistan ranks 98th in the Transparency International corruption index. In 1999, the total value of Pakistan’s stock market was less than $US 7 billion.
IV. Conclusion
Our empirical evidence comports neatly with the theoretical prediction of Grossman and Stiglitz (1980) that when information is costly some investors will earn greater expected profits than others. Institutions, which are on average the likely informed traders in financial markets, profit on their private information, while individuals, who are on average the likely uninformed traders in financial markets, incur trading losses. Before commissions and transaction taxes, the average daily institutional gain (and individual loss) is $NT 178 million. We estimate that, net of transaction costs, trading gains provide a performance boost of one percentage point annually to aggregate portfolio of institutional investors, while trading losses extract a penalty of 3.5 percentage points annually on the aggregate portfolio of individual investors.
Our empirical results suggest institutions profit in two ways. First, they provide liquidity to uniformed investors, thereby generating predominantly short-term profits.
Second, they trade aggressively when they possess private information that indicates prevailing market prices are misaligned with their private estimate of value. The profits from aggressive trading accrue over longer horizons, as the private information of institutions is gradually revealed to market participants.
One puzzle remains. Why do individual investors willing incur such large net trading losses? We would expect uninformed investors to lose when trading with informed investors, but we would not expect them to incur transaction costs as high as those documented here. There are several reasons why uninformed investors might trade:
liquidity requirements, rebalancing needs, hedging demands, entertainment, and the mistaken belief that they are informed, that is, overconfidence. Individual investors might need to trade to liquidate a portion of their portfolio or to invest savings, they might adjust the risk of their portfolios by rebalancing, or they might trade in order to hedge non-portfolio risks. It strikes us as unlikely that the liquidity, rebalancing, and hedging needs of Taiwanese investors account for annual turnover rates in excess of 300 percent annually. Why would liquidity, rebalancing, and hedging require more than four times as
much trading in Taiwan as in the US? Furthermore, liquidity, rebalancing, and hedging cannot explain the popularity of day trading in Taiwan.
Perhaps individual investors enjoy trading and receive utility from playing the game – even though they lose. This is a real possibility in the Taiwan market. Trading rooms are prevalent throughout Taiwan. Individual investors congregate daily at these venues affording an opportunity for social interaction. If entertainment motivates the trading of individuals, one can interpret our results as the price tag for this entertainment.
Finally, overconfidence can explain the trading losses incurred by individual investors. Odean (1998), Gervais and Odean (2001), and Caballé and Sákovics (2003) develop theoretical models of financial markets where investors suffer from overconfidence. These overconfidence models predict that investors will trade to their detriment.23 It is well documented that people tend to be overconfident (e.g., Alpert and Raiffa (1982), Griffen and Tversky (1992); see Odean (1998) for a more detailed review).
Thus, overconfidence can explain the trading losses incurred by individuals.
Our empirical analysis cannot clearly distinguish between trading for entertainment and trading due to overconfidence. If investors trade solely for entertainment, they knowingly and happily incur losses in exchange for entertainment, with no detrimental effect on their utility. If trading is driven by overconfidence, individuals inadvertently incur losses, which reduces their overall utility. Both explanations are plausible in our setting and neither excludes the other. Our empirical findings on the profitability of aggressive and passive trading by individuals offer some illumination. Virtually all trading losses by individuals can be traced to their aggressive trading. If entertainment is the sole explanation for individual investor trading losses, this result suggests individual investors find aggressive trading more entertaining than passive
23 In an exception to this finding, Kyle and Wang (1997) argue that when traders compete for duopoly profits, overconfident traders may reap greater profits. This prediction is based on several assumptions that do not apply to individuals trading common stocks. Benos (1998) has a similar result. Daniel, Hirshleifer, and Subrahmanyam (1998) consider the asset price implications of overconfidence but do not directly address investor welfare.
trading. If overconfidence is the sole explanation, this suggests individuals trade more aggressively when they are overconfident. This is consistent with theoretical models of overconfident investors (e.g., Odean, 1998) and, in our opinion, a plausible explanation of these results.
In poker, professional players will beat amateur players most of the time. Not on every hand, but through the course of an evening’s game, the professional will usually come out ahead. This is because professional players possess better bluffing skills and better information about probability outcomes. Similarly, in financial markets, we provide compelling evidence that professional (institutional) investors beat amateur (individual) investors. This is almost certainly because professional investors possess some combination of better information and better skill at processing and utilizing information. Amateur (individual) investors lose either because they enjoy doing so or because they are overconfident about their ability to play the game.
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Table 1: Basic Descriptive Statistics for Taiwan Stock Exchange
The market index is a value-weighted index of all stocks traded on the TSE. Mean market cap is calculated as the sum of daily market caps divided by the number of trading days in the year. Turnover is calculated as half the value of buys and sells divided by market cap. Number of traders and number of trades are from the TSE dataset. Day trades are defined as purchases and sales of the same stock on the same day by one investor. Day trade percentage of all trades is based on value of trade; percentages based on number of trades are similar.
Year
Return
%
Listed firms
Mean Market Cap
(bil TW $)
Turnover
%
No. of Traders
(000)
No. of Trades (000)
Day Trade as % of All
trades
1995 -27.4 347 5,250 195 1,169 120,115 20.6
1996 33.9 382 6,125 214 1,320 149,197 17.3
1997 18.2 404 9,571 393 2,173 310,926 24.8
1998 -21.6 437 9,620 310 2,816 291,876 25.6
1999 31.6 462 10,095 292 2,934 321,926 21.8
Mean
1995–99 18.5 8,132 294 2,082 238,808 23.1
Table 2: Descriptive Statistics by Trader Type Data are from the Taiwan Stock Exchange.
Value of Trade
($NT billion) Average Trade Size ($NT)
1996 11,453.8 11,456.6 165,550 166,006 89.0
1997 33,621.3 33,466.0 229,759 229,951 90.7
1998 26,479.1 26,427.4 193,327 194,158 89.3
1999 25,567.1 25,738.9 171,276 172,982 87.6
1995-99 106,323.4 106,344.1 190,656 191,459 89.5
Corporations
1995 348.4 323.4 327,158 312,644 3.3
1996 581.5 610.7 344,869 345,908 4.6
1997 1,543.5 1,587.2 452,509 456,975 4.2
1998 1,398.5 1,458.9 384,934 379,410 4.8
1999 1,206.2 1,354.3 341,054 343,014 4.4
1995-99 5,078.1 5,334.4 380,900 379,232 4.4
Dealers
1995 99.8 108.1 354,772 365,077 1.0
1996 147.6 146.5 339,957 362,339 1.1
1997 492.4 494.2 502,183 497,004 1.3
1998 444.1 459.9 416,719 395,555 1.5
1999 565.6 538.8 414,897 386,721 1.9
1995-99 1,749.5 1,747.4 424,131 411,109 1.5
Foreigners
1995 151.2 102.1 272,980 257,608 1.3
1996 277.7 229.7 299,642 270,225 2.0
1997 574.8 593.7 414,597 357,837 1.6
1998 532.6 502.9 370,258 317,170 1.7
1999 967.3 638.5 340,698 294,654 2.7
1995-99 2,503.5 2,066.9 350,413 310,439 1.9
Mutual Funds
1995 264.5 277.1 359,597 329,793 2.7
1996 414.1 431.2 359,375 317,638 3.3
1997 762.6 853.5 525,668 448,469 2.2
1998 768.4 773.6 448,118 366,122 2.6
1999 984.1 1,019.9 406,670 325,784 3.4
1995-99 3,193.7 3,355.3 427,355 359,068 2.8
All Investors
1995 10,065.8 10,065.8 171,925 171,911 100
1996 12,874.7 12,874.7 175,439 175,427 100
1997 36,994.6 36,994.6 240,910 240,904 100
1998 29,622.7 29,622.7 204,552 204,550 100
1999 29,290.3 29,290.3 183,715 183,715 100
1995-99 118,848.1 118,848.1 201,524 201,519 100
Table 3: Market Risk Premium and Factor Portfolio Returns in Taiwan The market risk premium is the return on a value-weighted Taiwan market index less the return on the riskfree asset. SMBt is the return on a value-weighted portfolio of small stocks minus the return on a value-weighted portfolio of big stocks, HMLt is the return on a weighted portfolio of high book-to-market stocks minus the return on a value-weighted portfolio of low book-to-market stocks, and WMLt is the return on a weighted portfolio of stocks with high recent returns minus the return on a value-weighted portfolio of stocks with low recent returns. The size and book-to-market factors are constructed identically to the U.S. factors of Fama and French (1993). The momentum factor is constructed assuming a six-month formation period and six-month holding period.
Market Risk Premium
Small Firm Premium
(SMB)
Value Premium
(HML)
Momentum Premium
(WML) Panel A: January 1983 to December 2002
Mean Monthly Return (%) 1.14 -0.07 0.39 -0.07
t-statistic 1.47 0.01 0.71 -0.15
Panel B: January 1995 to December 1999
Panel B: January 1995 to December 1999