By LARRY SWEDROE
While institutions are generally considered to be informed investors, individuals (retail investors) are generally considered to be noise traders. These are investors whose decisions to buy or sell are based on factors they believe to be helpful but in reality will give them no better returns than random choices) Noise traders tend to be emotion-driven, impulsive, reactive and herd-like.
The research (see here and here) has also shown that investor sentiment has significant effects on the cross-section of stock prices — it plays a significant role in international market volatility and generates return predictability of a form consistent with the correction of investor overreaction; and total sentiment is a contrarian predictor of country-level market returns, as high investor sentiment predicts low future returns and vice versa. In particular, smaller firms or firms with characteristics that have a great deal of uncertainty are likely to be most sensitive to speculative demands and more affected by shifts in investor sentiment. Greater uncertainty about stocks and their fundamentals can lead to investor overconfidence and psychological biases.
Let’s examine the research on the impact of confusing “noise” with valuable information. Brad Barber and Terrance Odean’s study All that Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors hypothesised that individual investors are likely to be net buyers of what they called “attention-grabbing” stocks. They found that individuals made nearly twice as many purchases as sales of stocks experiencing unusually high trading volume. They also found that individual investors tended to be net buyers of both the previous day’s big winners and big losers. Following the same pattern, they found that individual investors also tended to be net buyers of companies on days those companies were in the news — whether the news was good or bad.
Unfortunately for individual investors, they fail to recognize how efficient markets work. They fail to understand the information grabbing their attention is already incorporated into the price of the stock—and the speed of the stock market’s response to new information is startling. A study on the after-trading hours quarterly earnings announcements of 100 NYSE and 100 Nasdaq firms found that the majority of the price response was realized during the opening trade. For earnings announcements that occurred during trading hours, the results were not much different. For NYSE stocks the price adjustment occurred during the first several post-announcement trades. For Nasdaq stocks the price adjustment was concentrated in the very first post-announcement trade.
The result is that investors make the mistake of confusing information (the attention-getting news) with knowledge they can use to buy an undervalued (mispriced) stock. This leads to the poor trading results that Barber and Odean have consistently found in their series of studies on individual investors (for example here, here and here).
Fenghua Wen, Longhao Xu, Guangda Ouyang and Gang Kou contribute to the behavioural finance literature with their study Retail Investor Attention and Stock Price Crash Risk: Evidence From China, published in the October 2019 issue of the International Review of Financial Analysis. In it they explored the impact of retail investor attention (RIA) on crash risk — the likelihood of an extreme price collapse of a stock — in the Chinese stock market. They began by noting that as the largest emerging stock market in the world, the Chinese stock market provides an ideal platform for this goal:
Unlike fully developed stock markets such as the ones in U.S., where a majority of transactions occur among institutional investors, the Chinese stock market is dominated by retail investors with higher risk appetites.
The Chinese stock market still has imposed strict short-sale constraints that can lead to overpricing because only optimists can fully express their views.
To proxy for RIA, they developed a composite measure using social media data for the China stock market. They collected five proxies for investor attention that have been separately employed in prior studies:
The number of posts on the Guba Eastmoney Forum
Baidu Search Volume
Hexun RIA index
The number of times a stock is mentioned in news on Sina Finance
Trading volume
Their data covered a large sample of Chinese listed firms from 2006 to 2017. Following is a summary of their findings:
RIA in the China stock market positively and significantly relates to future crash risk — the higher the RIA, the higher the stock’s future crash risk.
RIA affects crash risk through the net-buys by retail investors.
The attention effect is stronger for non-state-owned, small-cap, young, high-turnover, high-volatility, low-institutional-ownership firms and firms with lower analyst coverage.
Stocks with higher book-to-market (value stocks) or higher profitability (quality stocks) are less likely to experience price crashes in the future.
The RIA effect on crash risk is substantially weaker for shortable stocks — with binding short-sale constraints, overreaction could strengthen short-term overpricing (causing greater crash risk), which will eventually be corrected in the long run as investors observe future news and realise their errors.
Wen, Xu, Ouyang and Kou noted that their findings are consistent with prior research on retail investors that has found:
Attention is a scarce resource, and when there are many alternatives, choices that attract attention are more likely to be chosen.
Limited attention not only limits learning and the decision-making process but also affects trading behaviour.
Retail investors tend to attach more weight to information they pay attention to, which induces them to net-buy the corresponding stocks in the short term due to their limited cognitive ability and nontrivial search costs.
The RIA effect on the net-buys by retail investors is significantly positive for stocks on the day immediately following their appearances on the Dragon-Tiger List (stocks experiencing extreme changes in their prices and trading volumes) — appearing on the Dragon-Tiger List induces net-buys by retail investors.
Their findings led the authors to conclude that RIA increases future crash risk and that the attention-induced trading behaviour of retail investors acts as a linkage from investor attention to future crash risk.
Investor takeaway
Research has demonstrated that individual investors generate negative results by paying attention to the noise of the market even before the costs of the trades. In addition, their behaviour induces increased crash risk in the stocks they buy. Investors should have learned that lesson from the crash of the dot-com stocks in March 2000.
A more recent example is that while the S&P 500returned about 25 percent through December 13, 2021, the ARK Innovation Fund (ARKK)experienced a “crash,” being down about 26 percent (and ranked in the 100th percentile in terms of performance) — investors tend to repeat the same mistakes, failing to learn from prior ones.
The bottom line is that the evidence shows that if investors ignored the noise, not only would they earn better returns, but they would also lead more productive lives, getting to spend their time on more important issues than trying to beat the market.
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