By LARRY SWEDROE
Behavioural finance professors Brad Barber and Terrance Odean have done extensive research on the performance and habits of individual investors. Among their findings is that, on average, individual investors lose money from trading — and not all the losses can be explained by trading costs. In their 2008 study All that Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors, they made the case that limited attention prevents retail investors from considering all available information and possible stock choices.
Instead, many retail investors choose stocks to buy from the subset of stocks that catch their attention. Because most investors own only a few stocks and do not sell short, limited attention plays a smaller role in their sales decision.
Barber and Odean, with co-authors Xing Huang and Chris Schwarz, add to the behavioural finance literature with their November 2020 study Attention Induced Trading and Returns: Evidence from Robinhood Users. Robinhood was the first to introduce commission-free trading, and its application makes it extremely easy. The authors noted: “Robinhood’s app is simple and engaging, designed to encourage people to invest. Robinhood added features to make investing more like a game. New members were given a free share of stock, but only after they scratched off images that looked like a lottery ticket.” This is important because their prior research had demonstrated that investors who access easier trading by switching from phone-based to online trade more and perform worse for up to two years after switching.
Drawing on their prior research, Barber, Odean, Huang and Schwarz hypothesised: “When buying stocks, investors with accounts at Robinhood are likely to be more influenced, both individually and as a group, by limited attention than other investors for several reasons”:
— Half of Robinhood users are first-time investors who are unlikely to have developed their own clear criteria for buying a stock.
— Inexperienced stock investors are likely to be more heavily influenced by attention and by biases that lead to return chasing.
— The Robinhood app directs Robinhood users’ attention to the same small subset of stocks, such as the 20 “Top Movers,” while offering limited additional information that might lead to more heterogeneous choices.
— The simplification of information on the Robinhood app is likely to provide cognitive ease to investors, leading them to rely more on their intuition and less on critical thinking.
— Robinhood users may deliberate and hesitate less than other investors when trading due to a lack of frictions because it is easy to place trades on the app and commissions are zero.
— As evidenced by turnover rates many times higher than at other brokerage firms, Robinhood users are more likely to be trading speculatively and less likely to be trading for reasons such as investing their retirement savings, liquidity demands, tax-loss selling and rebalancing. The lack of non-speculative trading motives increases the potential for attention-driven trading.
— Because Robinhood users are more likely than other investors to be influenced by attention, their purchase behavior is more likely to be correlated; that is, they herd more than other investors.
Their analysis focused on examining abnormal returns following events in which the number of Robinhood users owning a particular stock increased dramatically in one day. While herding by a few investors is unlikely to move prices in all but the least liquid stock, by May 2020, there were 13 million Robinhood users, more users than Schwab (12.7 million) or E-Trade (5.5 million).
Additionally, Robinhood users are unusually active. In the first quarter of 2020, Robinhood users “traded nine times as many shares as E-Trade customers, and 40 times as many shares as Charles Schwab customers, per dollar in the average customer account in the most recent quarter.” Their data set is from the Robintrack website, which scrapes stock popularity data from Robinhood between May 2, 2018, and August 13, 2020. The following is a summary of their findings:
— Robinhood users are more subject to attention biases and more likely to chase stocks with extreme performance and volume than other retail investors — for Robinhood users about 35 (25) percent of all net buying (selling) was in the top 10 stocks versus 24 (14) percent for other retail investors.
— Robinhood herding is influenced by information that is prominently displayed on the Robinhood app.
— There is persistence in the herding episodes: a stock which was heavily bought by Robinhood investors was 10 percent more likely to experience another episode the next day. However, negative returns were less likely to generate extreme herding.
— Robinhood herding can be forecasted by attention measures, such as lagged absolute returns and lagged abnormal volume, previously shown to affect the buy-sell imbalances of retail investors.
— When Robinhood experienced outages, they observed the largest decrease in retail trading among stocks that attract the attention of Robinhood users (the most popular stocks on Robinhood and stocks with a high probability of a herding event).
— Robinhood users are more aggressive buyers of stocks on Robinhood’s Top Mover list than other retail investors — Robinhood investors buy both extreme gainers and losers, while other retail investors prefer to buy extreme gainers rather than losers.
— Robinhood herding episodes are followed by abnormal negative returns. Defining herding events as the top 0.5 percent of positive user changes as a percent of prior day user count each day, or a user increase of more than 1,000 and more than 50 percent relative to the previous day, the return and user patterns are similar over a 31-day period from 10 trading days before the event day to 20 trading days after — average abnormal return on the herding day was 14 percent (42 percent). Most of the abnormal return occurred at the open of trading — the mean opening return was 11 percent. Despite the large positive mean daily returns, about one-third of the stocks had large negative returns on the day of herding events. However, over the subsequent month, the average return was about -5 percent (-9 percent). These results are economically and statistically significant and were not driven by just a few stocks. In addition, portfolio alphas were more negative during the 2020 pandemic period, ranging from -79 to -94 basis points per day.
— Returns were also negative following a day when they observed both a surge in Robinhood users and the stock’s price went down.
— A strategy of selling after a Robinhood herding event and repurchasing five days later would have resulted in a return of 3.5 percent (6.4 percent for extreme herding events). For the 4,884 herding events observed, this strategy would have yielded a positive return 63 percent of the time.
— Returns were negative following Robinhood herding events for stocks with market caps under $1 billion but not for stocks with market caps over $1 billion.
— Retail trading has increased significantly at Robinhood and elsewhere in the post-Covid period (after March 13, 2020), and the negative return effect following Robinhood herding events is more pronounced in the post-Covid period.
Barber, Odean, Huang and Schwarz observed that sophisticated investors could exploit the patterns created by Robinhood investors by shorting stocks, or buying puts, in response to Robinhood herding events. In fact, they found a marked increase in short selling for stocks involved in Robinhood herding events — for the stocks with the top 25 returns for the period, the average change in short interest was three times greater. They concluded that their results “suggest strongly that market participants examined Robinhood ownership data, knew about the subsequent poor performance caused by Robinhood herding, and traded against Robinhood order flow.”
Another interesting finding was that the average number of stocks held by Robinhood investors was just three, displaying a lack of knowledge of the benefits of diversification. The lack of diversification could be explained by the all-too-human trait of overconfidence.
Their findings led, Barber, Odean, Huang and Schwarz to conclude: “Large increases in Robinhood users are often accompanied by large price spikes and are followed by reliably negative returns. While some users profit from these episodes, we find that, in aggregate, Robinhood users who establish new positions during these episodes incur losses.”
They added that their findings contribute to the literature demonstrating price reversals following attention-grabbing events such as Jim Kramer’s stock recommendations, Google stock searches and repeat news stories. This result “fits into the emerging literature that emphasises the display of information can affect investor behaviour.” (Note: Robinhood discontinued the reporting of stock popularity data on August 13, 2020.)
The above findings are entirely consistent with those from the 2014 study The Cross-Section of Speculator Skill: Evidence from Day Trading. Co-authored with Yi-Tsung Lee and Yu-Jane Liu, Barber and Odean studied the performance of day traders (almost exclusively individual investors) in Taiwan (where there were about 450,000 day traders) for the 15-year period 1992 to 2006.
Among their findings was that the vast majority of day traders lose money: “While about 20% earn profits net of fees in the typical year, the results of our analysis suggest that less than 1% of day traders (4,000 out of 450,000) are able to outperform consistently.” The other 99 percent would be better off abandoning their day-trading efforts. In other words, day-trading is hazardous to your financial health.
Summary
Robinhood, with commission-free trading, has certainly been successful in its stated mission, having attracted 13 million users with its app that makes trading easy. Unfortunately, its application also leaves naïve individual investors more susceptible to well-documented biases that lead to speculative trading and poor results, with the winner being Robinhood itself.
The historical evidence on efforts of individual investors to generate alpha clearly show that while it’s not impossible to generate alpha on a consistent basis, the odds of doing so are so poor it’s not prudent to try. In other words, if you look in the mirror and see Warren Buffett, go ahead and try to pick stocks that will outperform.
But unless you live in Lake Wobegon, where everyone has Buffett-like abilities, you’re not likely to see the Oracle of Omaha in the mirror. For those who don’t, the winning strategy is to build a globally diversified portfolio that reflects your unique ability, willingness and need to take risk, and stay the course, rebalancing and tax managing as events dictate.
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