Terrance Odean

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.

The Behavior of Individual Investors

We provide an overview of research on the stock trading behavior of individual investors. This research documents that individual investors (1) underperform standard benchmarks (e.g. a low-cost index fund), (2) sell winning investments while holding losing investments (the “disposition effect†), (3) are heavily influenced by limited attention and past return performance in their purchase decisions, (4) engage in naA¯ve reinforcement learning by repeating past behaviors that coincided with pleasure while avoiding past behaviors that generated pain, and (5) tend to hold undiversified stock portfolios. These behaviors deleteriously affect the financial well being of individual investors.

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.

Are Individual Investors Tax Savvy? Evidence from Retail and Discount Brokerage Accounts

Using brokerage account data, we analyze the tax awareness of individual investors. We find strong evidence that taxes matter: investors prefer to locate bonds and mutual funds in retirement accounts and, in December, harvest stock losses in their taxable accounts. However, investors also trade actively in their taxable accounts, realize gains more frequently than losses, and locate a material portion of their bonds in taxable accounts. Though taxes leave clear footprints in the data we analyze, many investors could improve their after-tax performance by fully capitalizing on the tax avoidance strategies available to equities, while optimally locating their assets.

Good Reasons Sell: Reason-Based Choice Among Group and Individual Investors in the Stock Market

In this paper, we compare the investment decisions of groups (stock clubs) and individuals. Both individuals and clubs are more likely to purchase stocks that are associated with good reasons (e.g., a company that is featured on a list of most-admired companies). However, stock clubs favor such stocks more than individuals, despite the fact that such reasons do not improve performance. We describe why social dynamics may make good reasons more important for groups than individuals.

Do Noise Traders Move Markets

We study the trading behavior of individual investors using the Trade and Quotes (TAQ) and Institute for the Study of Security Markets (ISSM) transaction data over the period 1983 to 2001. We document four results: (1) Order imbalance based on buyer- and sellerinitiated small trades from the TAQ/ISSM data correlates well with the order imbalance based on trades of individual investors from brokerage firm data. This indicates trade size is a reasonable proxy for the trading of individual investors. (2) Order imbalance based on TAQ/ISSM data indicates strong herding by individual investors. Individual investors predominantly buy (sell) the same stocks as each other contemporaneously. Furthermore, they predominantly buy (sell) the same stocks one week (month) as they did the previous week (month). (3) When measured over one year, the imbalance between purchases and sales of each stock by individual investors forecasts cross-sectional stock returns the subsequent year. Stocks heavily bought by individuals one year underperform stocks heavily sold by 4.4 percentage points in the following year. For stocks for which it is most difficult to arbitrage mispricings, the spread in returns between stocks bought and stocks sold is 13.1 percentage points the following year. (4) Over shorter periods such as a week or a month, a different pattern emerges. Stocks heavily bought by individual investors one week earn strong returns in the subsequent week, while stocks heavily sold one week earn poor returns in the subsequent week. This pattern persists for a total of three to four weeks and then reverses for the subsequent several weeks. In addition to examining the ability of small trades to forecast returns, we also look at the predictive value of large trades. In striking contrast to our small trade results, we find that stocks heavily purchased with large trades one week earn poor returns in the subsequent week, while stocks heavily sold one week earn strong returns in the subsequent week.

Bubbling with Excitement: An Experiment

Anecdotal and indirect empirical evidence suggest that excitement and market bubbles are intertwined, such that excitement not only arises during bubbles but may also help fuel them. We directly test the impact of excitement on bubbles in a bubble-prone experimental asset-pricing market (Capinalp, Porter, and Smith, 2001). Prior to trading, participants are assigned to emotion inductions through video clips The results of fifty-five markets show larger asset pricing bubbles in magnitude and amplitude in the excitement treatment relative to a treatment of same valence and lower intensity (calm) and a treatment of similar intensity and opposite valence (fear).

Chapter 22 – The Behavior of Individual Investors *

We provide an overview of research on the stock trading behavior of individual investors. This research documents that individual investors (1) underperform standard benchmarks (e.g. a low-cost index fund), (2) sell winning investments while holding losing investments (the “disposition effect”), (3) are heavily influenced by limited attention and past return performance in their purchase decisions, (4) engage in naive reinforcement learning by repeating past behaviors that coincided with pleasure while avoiding past behaviors that generated pain, and (5) tend to hold undiversified stock portfolios. These behaviors deleteriously affect the financial well being of individual investors.

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.

Does Online Trading Change Investor Behavior

We appreciate the comments of an anonymous reviewer, Franklin Allen, Randy Beatty, Ken French, Ravi Jaganathan, Cesare Robotti, Chuck Schnitzlein, Michael Vetsuypens, and seminar participants at the Berkeley Program in Finance (November 1999), National Bureau of Economic Research Behavioral Finance Group (December 1999), the European Finance Association meetings, Princeton, the Maryland Finance Symposium, the Review of Financial Studies Behavior Finance Conference, the Securities and Exchange Commission, Southern Methodist University, UC-Berkeley, the University of Iowa, the University of Utah, the Vanderbilt Law School Conference on Corporate and Securities Law, the Western Finance Association meetings (June 2000) and Yale University. Michael Foster provided valuable research assistance. This article is an adaptation of Barber and Odean (2002), which previously appeared in the Review of Financial Studies. All errors are our own.