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 trading profits of
$NT 178 million plus another $NT 46.4 million in market-timing profits ($US 7.6 million total), 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 less comprehensive samples of U.S.
individuals indicate an underperformance of 20 basis points or more per month before deducting commissions and bid-ask spreads (Odean (1999), Barber and Odean (2001)). We estimate that the net trading and market-timing losses of Taiwanese individuals detract 3.8 percentage points a year from performance. Barber and Odean (2000) estimate that net trading losses of U.S. individuals (ignoring possible market-timing losses and capital gains taxes) detract 1.9 percentage points a year from the aggregate investor portfolio return and 2.3 percentage points from the return of the average investor.
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.21 Thus, the high incidence of day trading does not appear to be unique to Taiwan.
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.
Turnover on the NYSE averaged 97 percent annually from 2000 through 2003 while turnover on Nasdaq during the same period averaged over 175 percent (after adjusting for double counting). Thus, Taiwanese investors in our sample traded two to three times as actively as do current U.S. investors. Individual investors in Taiwan may trade more actively because they find trading more enjoyable than their American counterparts and are thus willingly incur large losses for entertainment. Or they may trade more actively because they are more overconfident.22 Since Taiwanese individual investors trade 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 active 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 institutional investors are profiting from information, not simply from their willingness to supply liquidity. Such an information advantage would be profitable even in the US where individual investors are less exuberant. However, it is possible that the active trading of Taiwanese individuals creates greater mispricings that are subsequently exploited by institutions.
21 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.
22 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).
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).23 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.
IV. Conclusion
We estimate that the trading and market-timing losses, including costs, on the aggregate portfolio of individual investors are equivalent to 3.8 percentage points annually.
23 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
Put differently, these costs are roughly equal to 2.2 percent of Taiwan’s gross domestic product during our sample period. Before commissions and transaction taxes, the average daily institutional gain from trade and market-timing is $NT 224 million. We estimate that, net of transaction costs, trading and market-timing gains provide a performance boost of 1.5 percentage points annually to the aggregate portfolio of institutional 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 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. Turnover in Taiwan is about 300 percent annually and two to three times that observed in the U.S in recent years. It strikes us as unlikely that the liquidity, rebalancing, and hedging needs of Taiwanese investors are two to three times those of current U.S investors. From 1940 through 1970, annual turnover on the NYSE was a mere 16 percent. It is similarly implausible that the liquidity, rebalancing, and hedging needs of contemporary U.S.
investors are six times that of U.S. investors during the mid-twentieth century.
Undoubtedly, a great deal of current trading in Taiwan and the U.S. is speculative.
There are two reasons for uninformed investors to trade speculatively:
overconfidence and entertainment. 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). Odean (1998), Gervais and Odean (2001), and Caballé and Sákovics (2003) develop theoretical models in which overconfident investors trade to their detriment.24 Investors in our sample may simply be overconfident in their trading ability and their information; they expect to profit from trading even though, on average, they don’t. Alternatively, some investors may simply enjoy trading, even though they expect, on average, to lose. Quite likely many investors both are overconfident and enjoy trading. For these investors, overconfidence probably contributes, in the short-run, to their enjoyment. Our empirical analysis cannot distinguish between trades motivated by overconfidence and trades motivated by entertainment. To the extent that investors do trade for entertainment, our results can be interpreted as the price tag for this entertainment.
In many countries, privatized social security programs and defined contribution retirement plans (such as 401(k) plans) increasingly require that workers make investment decisions and bear investment risks for their retirement savings. Most workers have no training in investments. Individual investors make poor trading decisions, underdiversify their portfolios, and manage capital gains taxes sub-optimally. Many workers increase, rather than diversify, risk by holding their own company stock in retirement accounts. We document that trading losses and costs reduce the returns of individual investors in Taiwan by 3.8 percentage points a year, more than the average annual return of the Taiwanese market during our sample period. Less comprehensive studies suggest that trading losses and costs for individual investors in the U.S. are about 2 percentage points a year. Over a savings horizon of twenty or more years, an annual return shortfall of 2 to 3.8 percentage points will result in a tremendous reduction in a worker’s retirement wealth. In Taiwan, the U.S., and elsewhere, individuals need to be educated about best investment practices. Until
24 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.
they are, the answer to “Who losses from trade?” remains, unequivocally: individual investors.
References
Ackermann, Carl, Richard McEnally, and David Ravenscraft, 1999, The performance of hedge funds: Risk, return, and incentives, Journal of Finance, 54, 833-874.
Agrawal, Vikas, and Narayan Y. Naik, 2000, On taking the alternative route: The risks, rewards, and performance persistence of hedge funds, Journal of Alternative Investments, 2, 6-23.
Alpert, Marc, and Howard Raiffa, 1982, A progress report on the training of probability assessors, in Daniel Kahneman, Paul Slovic, and Amos Tversky, eds.: Judgment Under Uncertainty: Heuristics and Biases, (Cambridge University Press, Cambridge and New York).
Amin, Gaurav S., and Harry M. Kat, 2003, Hedge fund performance 1990-2000: Do the “money machines”
really add value?, Journal of Financial and Quantitative Analysis, 38, 251-274.
Barber, Brad M., and Terrance Odean, 2000, Trading is hazardous to your wealth: The common stock investment performance of individual investors, Journal of Finance, 2000, Vol. 55, No. 2, p.773-806.
Barber, Brad M., and Terrance Odean, 2001, Boys will be boys: Gender, overconfidence, and common stock investment, Quarterly Journal of Economics, 116, 261-292.
Barber, Brad M., Yi-Tsung Lee, Yu-Jane Liu, and Terrance Odean, 2004, Do individual day traders make money? Evidence from Taiwan, working paper, UC-Davis, Davis, CA.
Benos, Alexandros V., 1998, Aggressiveness and survival of overconfident traders, Journal of Financial Markets, 1, 353-383.
Brown, Stephen J., William N. Goetzmann, and Roger G. Ibbotson, 1999, Offshore hedge funds: Survival and performance, 1989-95, Journal of Business, 72, 91-117.
Caballé, Jordi, and József Sákovics, 2003, Speculating against an overconfident market, Journal of Financial Markets, 6, 199-225.
Carhart, Mark M., 1997, On persistence in mutual fund performance, Journal of Finance, 52, 57-82.
Chan, Hsiu-Lang, Narasimhan Jegadeesh, and Russ Wermers, 2000, The value of active mutual fund management: an examination of the stockholdings and trades of fund managers, Journal of Financial and Quantitative Analysis, 35, 343-368.
Choe, Hyuk, Bong-Chan Kho, and René Stulz, 1999, Do foreign investors destabilize stock markets? The Korean experience in 1997, Journal of Financial Economics, 54, 227-264.
Christopherson, Jon A., Wayne E. Ferson, and Debra A. Glassman, 1998, Conditional measures of performance and persistence for pension funds, In: Research in Finance, Vol. 16, JAI Press, Stamford, CT, pp. 1-46.
Cohen, Randolph B., Paul A. Gompers, and Tuomo Vuolteenaho, 2002, Who underreacts to cash-flow news?
Evidence from trading between individuals and institutions, forthcoming, Journal of Financial Economics.
Coggin, T. Daniel and Charles A. Trzcinka, 2000, A panel study of U.S. equity pension fund manager style performance, Journal of Investing, 9, 6-12.
Coggin, T. Daniel, Frank J. Fabozzi, and Shafiqur Rahman, 1993, The investment performance of U.S.
equity pension fund managers: An empirical investigation, Journal of Finance, 48, 1039-1055.
Coval, Joshua D., and Tobias J. Moskowitz, The geography of investment: Informed trading and asset prices, Journal of Political Economy, 2001, 109, 811-841.
Coval, Joshua D., David Hirshleifer, and Tyler Shumway, 2003, Can individual investors beat the market, unpublished working paper, Harvard Business School, Cambridge, MA.
Daniel, Kent, David Hirshleifer, and Avanidar Subrahmanyam, 1998, Investor psychology and security market under- and overreactions, Journal of Finance, 53, 1839-1885.
Daniel, Kent, Mark Grinblatt, Sheridan Titman, and Russ Wermers, 1997, Measuring mutual fund performance with characteristic-based benchmarks, Journal of Finance, 52, 1035-1058.
Delguercio, Diane, and Paula A. Tkac, 2002, The determinants of the flow of funds of managed portfolios:
Mutual funds vs. pension funds, Journal of Financial and Quantitative Analysis, 37, 523-557.
Fama, Eugene F., 1991, Efficient capital markets II, Journal of Finance 46, 1575-1618.
Fama, Eugene F., and Kenneth R. French, 1993, Common risk factors in returns on stocks and bonds, Journal of Financial Economics, 33, 3-56.
Fama, Eugene F. and Kenneth R. French, 2004, Disagreement, tastes, and asset prices, Tuck Business School Working Paper No. 2004-03. http://ssrn.com/abstract=502605
Ferson, Wayne and Kenneth Khang, 2002, Conditional performance measurement using portfolio weights:
Evidence for pension funds, Journal of Financial Economics, 65, 249-282.
Gervais, Simon, Ron Kaniel, and Dan H. Mingelgrin, 2001, The high-volume return premium, Journal of Finance, 56, 877-922.
Gervais, Simon, and Terrance Odean, 2001, Learning to be overconfident, Review of Financial Studies, 14, 1-27.
Griffin, Dale, and Amos Tversky, 1992, The weighing of evidence and the determinants of confidence, Cognitive Psychology, 24, 411-435.
Griffin, John M., Jeffrey H. Harris, and Selim Topaloglu, 2003, The dynamics of institutional and individual trading, Journal of Finance, 58, 2285-2320.
Grinblatt, Mark, and Sheridan Titman, 1989, Mutual fund performance: An analysis of quarterly portfolio holdings, Journal of Business, 62, 393-416.
Grinblatt, Mark, and Sheridan Titman, 1993, Performance measurement without benchmarks: An examination of mutual fund returns, Journal of Business, 66, 47-68.
Grinblatt, Mark and Matti Keloharju, 2000, The investment behavior and performance of various investor types: a study of Finland’s unique data set, Journal of Financial Economics, 55, 43-68.
Grossman, Sanford J. and Joseph E. Stiglitz, 1980, On the impossibility of informationally efficient markets, American Economic Review, 70, 393-408.
Ikenberry, David, Richard Shockley, and Kent Womack, 1998, Why active fund managers often underperform the S&P 500: The impact of size and skewness, Journal of Private Portfolio Management, 1, 13-26.
Ivkovich, Zoran, Clemens Sialm, and Scott J. Weisbenner, 2004, Portfolio concentration and the performance of individual investors, working paper, University of Illinois.
Ivkovich, Zoran, and Scott J. Weisbenner, 2004, Local does as local is: Information content of the geography of individual investors’ common stock investments, forthcoming, Journal of Finance.
Jensen, Michael C., 1968, The performance of mutual funds in the period 1945-1964, Journal of Finance, 23, 389-416.
Khwaja, Asim Ijaz, and Atif Mian, 2003, Trading in phantom markets: Price manipulation in an emerging stock market, working paper, University of Chicago, Chicago, IL.
Kyle, Albert S., 1985, Continuous Auctions and insider trading, Econometrica, 53, 1315-1335.
Kyle, Albert S., and F. Albert Wang, 1997, Speculation duopoly with agreement to disagree: Can overconfidence survive the market test?, Journal of Finance, 52, 2073-2090.
Lakonishok, Josef, Andrei Shleifer, and Robert Vishny, 1992, The structure and performance of the money management industry, Brookings Papers on Economic Activity: Microeconomics 1992, 330-391.
Lee, Ju-Whei, J. Frank Yates, Hiromi Shinotsuka, R. Singh, M. L. U. Onglatco, N. S. Yen, M. Gupta, and D.
Bhatnagar, 1995, Cross-national differences in overconfidence, Asian Journal of Psychology, 1, 63-69.
Liang, Bing, 1999, On the performance of hedge funds, Financial Analysts Journal, 55, 72-85.
Lyon, John D., Brad M. Barber, and Chih-Ling Tsai, Improved methods for tests of long-run abnormal stock returns, Journal of Finance 54, 165-201.
Mitchell, Mark L., and Erik Stafford, Managerial decisions and long-term stock price performance, Journal of Business 73, 287-329.
Odean, Terrance, 1998, Volume, volatility, price, and profit when all traders are above average, Journal of Finance 53, 1887-1934.
Odean, Terrance, 1999, Do investors trade too much?, American Economic Review, 89, 1279-1298.
Schlarbaum, Gary G., Wilbur G. Lewellen, and Ronald C. Lease, 1978a, The common-stock-portfolio performance record of individual investors: 1964-70, Journal of Finance 33, 429-441.
Schlarbaum, Gary G., Wilbur G. Lewellen, and Ronald C. Lease, 1978b, Realized returns on common stock investments: The experience of individual investors, Journal of Business 51, 299-325.
Seasholes, Mark S., 2000, Smart foreign traders in emerging markets, unpublished working paper, UC-Berkeley, UC-Berkeley, CA.
Wermers, Russ, 2000, Mutual fund performance: An empirical decomposition into stock-picking talent, style, transactions costs, and expenses, Journal of Finance, 55, 1655-1694.
Yates, J. Frank, Ju-Whei Lee, Hiromi Shinotsuka, Andrea L. Patalano, and Winston R. Sieck, 1998, Cross-cultural variations in probability judgment accuracy: Beyond general knowledge overconfidence, Organizational Behavior and Human Decision Processes, 74, 89-117.
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
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