Yi-Tsung Lee

Just How Much Do Individual Investors Lose by Trading

Individual investor trading results in systematic and economically large losses. Using a complete trading history of all investors in Taiwan, we document that the aggregate portfolio of individuals suffers an annual performance penalty of 3.8 percentage points. Individual investor losses are equivalent to 2.2% of Taiwans gross domestic product or 2.8% of the total personal income. Virtually all individual trading losses can be traced to their aggressive orders. In contrast, institutions enjoy an annual performance boost of 1.5 percentage points, and both the aggressive and passive trades of institutions are profitable. Foreign institutions garner nearly half of institutional profits. The Author 2008. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

Is the Aggregate Investor Reluctant to Realise Losses? Evidence from Taiwan

We ask whether the typical investor and the aggregate investor exhibit a bias known as the disposition effect, the tendency to sell investments that are held for a profit at a faster rate than investments held for a loss. We analyse all trading activity on the Taiwan Stock Exchange (TSE) for the five years ending in 1999. Using a dataset that contains all trades (over one billion) and the identity of every trader (nearly four million), we find that in aggregate, investors in Taiwan are about twice as likely to sell a stock if they are holding that stock for a gain rather than a loss. Eighty-four percent of all Taiwanese investors sell winners at a faster rate than losers. Individuals, corporations, and dealers are reluctant to realise losses, while mutual funds and foreigners, who together account for less than 5% of all trades (by value), are not.

Order Imbalances and Market Efficiency: Evidence from the Taiwan Stock Exchange

Data from the Taiwan Stock Exchange identify the originator of each submitted order, and there are no designated dealers or specialists. We study marketable order imbalances, i.e., the net order flow resulting from trades that demand immediacy. We distinguish imbalances by trader type (individuals, domestic institutions, foreign institutions) and by the usual size of each trader’s order. Day-to-day persistence in order imbalance is strongest for small foreign institutions and weakest for large individual traders. Such persistence emanates both from splitting orders over time and from herding, and there is little evidence that aggregate price pressures from such persistence last beyond a trading day, indicating that de facto market-making is quite effective. We attempt to discern which types of traders are de facto liquidity-providers, which are likely to be informed, and which trade for liquidity reasons. The evidence indicates that all trader classes are successful market-makers, large domestic institutions conduct the most informed trades, and large individuals are noise or liquidity traders.

Trading patterns of big versus small players in an emerging market: An empirical analysis

Abstract This study uses a Vector Autoregressive (VAR) model to examine interdependencies among institutional investors, big individual investors, and small individual investors, and the effects of their trading on stock returns on the Taiwan Stock Exchange (TSE). The results imply that, during the sample period, big individual investors are the most well informed players; their trading affects not only stock returns but also small individual investors. Small individual investors are not well informed and are slow learners. Their orders to trade tend to provide liquidity to institutional and big individual investors, but there is no compensation for their liquidity services. We find that institutional investors follow neither positive-feedback nor negative-feedback trading strategies. Overall, the responses to shocks, except for those of small individual investors, decay quickly, indicating that the TSE can absorb shocks quickly and efficiently. Our analysis implies that small individual investors would be better off institutionalizing their investment decisions (e.g., by investing in mutual funds).

Do Day Traders Rationally Learn About Their Ability

Rational models claim “trading to learn�? explains widespread excessive speculative trading and challenge behavioral explanations of excessive trading. We argue rational learning models do not explain speculative trading by studying day traders in Taiwan. Consistent with previous studies of learning, unprofitable day traders are more likely to quit than profitable traders. Consistent with models of overconfidence and biased learning (but not with rational learning), the aggregate performance of day traders is negative, 74% of day trading volume is generated by traders with a history of losses, and 97% of day traders are likely to lose money in future day trading.We analyze the performance of and learning by individual investors who engage in day trading in Taiwan from 1992 to 2006 and test the proposition that individual investors rationally speculate as day traders in order to learn whether they possess the superior trading ability. Consistent with models of both rational and biased learning, we document that unprofitable day traders are more likely to quit and that day traders begin with relatively small trades that increase as they gain experience. Inconsistent with models of rational speculation and learning, we document that the aggregate performance of day traders is negative and that over half of day trading can be traced to traders with considerable experience and a history of losses.