Swedroe: Ignore Investor Noise

Investor sentiment can drive mispricing; best to disregard it.

Investor sentiment—the propensity of individuals to trade on noise and emotions rather than facts—represents investors’ beliefs about future cash flows that the prevailing fundamentals cannot explain. Such activity can lead to mispricing. Eventually, any mispricing would be expected to be corrected when the fundamentals are revealed, making investor sentiment a contrarian predictor of stock market returns.

Examples of times when investor sentiment ran high are the 1968-69 electronics bubble, the biotech bubble of the early 1980s, and the dot-com bubble of the late 1990s. Sentiment fell sharply, however, after the 1961 crash of growth stocks, in the mid-1970s with the oil embargo, and in the crash of 2008.

Over roughly the last decade, researchers have explored investor sentiment’s impact on markets. Malcolm Baker and Jeffrey Wurgler have even constructed an investor sentiment index based on six metrics: trading volume as measured by NYSE turnover; the dividend premium (the difference between the average market-to-book ratio of dividend-payers and non-payers); the closed-end fund discount; number of IPOs; first-day returns on IPOs; and the equity share in new issues. (Data available at Wurgler’s New York University webpage.)

Does investor sentiment (the psychology of crowds) affect stock prices, leading to mispricings? The argument against the belief that investor sentiment affects stock prices is that any effects caused by sentiment should, in theory, be eliminated by rational traders seeking to exploit the profit opportunities created by mispricings. However, if there are limits to arbitrage, rational traders cannot fully exploit such opportunities—and sentiment effects become more likely.

The question then is, does investor sentiment predict overpriced or underpriced stock markets? Let’s review the evidence.

The Evidence

Baker, Wurgler and Yu Yuan, authors of the study, “Global, Local, and Contagious Investor Sentiment,” which appeared in the May 2012 issue of Journal of Financial Economics, investigated the effect of investor sentiment’s global and local components on major stock markets, both at the country average level and as they affect the time series of the cross section of stock returns.

They also studied whether sentiment spreads across markets. The study covered the period 1980 through 2005 and six stock markets: Canada, France, Germany, Japan, the United Kingdom and the United States. As previously mentioned, they compiled the first global sentiment index.

Following is a summary of their findings:

• Investor sentiment plays a significant role in international market volatility and generates return predictability of a form consistent with the correction of investor overreaction.
• Total sentiment, particularly the global component of total sentiment, is a contrarian predictor of country-level market returns—high investor sentiment predicts low future returns and vice versa. Results are similar for value-weighted and equal-weighted market returns and for non-U.S. markets.
• The economic significance of the effect is nontrivial. A one-standard-deviation increase in a country’s total investor sentiment index is associated with 3.5% per year lower value-weighted market returns and 4.3% per year lower equal-weighted returns.
• Global sentiment is the main driver of country-level results. A one-standard-deviation increase in the global sentiment index is associated with 5.4% per year lower value-weighted market returns and 5.6% per year lower equal-weighted market returns.
• Broad waves of sentiment have greater effects on hard-to-arbitrage (due to greater costs and greater risks) and hard-to-value (small-cap, high return volatility, growth and distressed) stocks. These stocks will exhibit high “sentiment beta.”
• After sorting stocks across years according to whether the level of their total sentiment index is positive or negative, top-volatility-decile stocks earn 16.1% per year lower returns when the year starts in a high-sentiment state—consistent with a correction of sentiment-driven overpricing. High-sentiment periods also portend 1% per month lower returns on the smallest capitalization portfolio, another economically large effect. The effect of sentiment is much smaller on low-volatility stocks or large stocks, as they are relatively easy to arbitrage and value.
• Not only does local and global sentiment predict the cross section of a country’s returns, but investor sentiment also is contagious. For instance, U.S. sentiment affects returns for countries linked with the United States by significant capital flows. This conclusion doesn’t depend on including the United States in the sample.

The authors concluded: “Global sentiment is a statistically and economically significant contrarian predictor of market returns. Both global and local components of sentiment help to predict the time series of the cross-section; namely, they predict the returns on high sentiment-beta portfolios such as those including high volatility stocks or stocks of small, distressed, and growth companies.”

Sentiment & Short Sales

Robert Stambaugh, Jianfeng Yu and Yu Yuan, authors of the study “The Short of It: Investor Sentiment and Anomalies,” which also appeared in the May 2012 issue of Journal of Financial Economics, investigated the presence of sentiment effects by combining two concepts prominent in the academic literature:

• Investor sentiment contains a marketwide component with the potential to influence prices on many securities in the same direction at the same time.
• Impediments to short selling play a significant role in limiting the ability of rational traders to exploit overpricing.

They explored whether sentiment-related overpricing is at least a partial explanation for 11 asset-pricing anomalies. These 11 asset-pricing anomalies reflect sorts on measures that include: financial distress (firms with high failure probability have lower, not higher, subsequent returns); net stock issuance (issuers underperform nonissuers); accruals (firms with high accruals earn abnormally lower returns on average than firms with low accruals); net operating assets (defined as the difference on a company’s balance sheet between all operating assets and all operating liabilities scaled by total assets, it is a strong negative predictor of long-run stock returns); momentum (high past recent returns forecast high future returns); gross profitability premium (more profitable firms have higher returns than less profitable ones); asset growth (companies that grow their total assets more earn lower subsequent returns); return on assets (more profitable firms have higher expected returns than less profitable firms); and investment-to-assets (higher past investment predicts abnormally lower future returns).

The authors hypothesized that the most optimistic investors are more likely to be too optimistic when investor sentiment is high than when it is low. As the measure of sentiment, they used a composite index that included the six Baker-Wurgler metrics. For each of the 11 anomalies, the authors analyzed the strategy that goes long stocks in the highest-performing decile and short those in the lowest-performing decile.

Following is a summary of their findings:

• Each anomaly is stronger following higher-than-median levels of investor sentiment. Ten of the 11 results were statistically significant at the 5% level (there was a 5% or less chance the results were random).
• When averaged across anomalies, 70% of the benchmark-adjusted profits from a long/short strategy occurred in months following levels of investor sentiment above its median value.
• When averaged across anomalies, 78% of the benchmark-adjusted profits from shorting that leg occur in months following high sentiment.
• As expected, there was little evidence of overpricing in the long leg of the portfolio. The reason is that even though stocks in the long leg could be overpriced when marketwide sentiment is high, it should contain the least degree of overpricing. None of the long legs in the 11 anomaly portfolios exhibited a significant difference (an average of just 0.04% per month) between high-sentiment and low-sentiment periods.

Stambaugh, Yu and Yuan cited other works that support their findings:

• The 2006 study “Investor Sentiment and the Cross-Section of Stock Returns” found that marketwide sentiment exerted stronger effects on difficult-to-value and hard-to-arbitrage stocks.
• The 2011 study “Investor Sentiment and the Mean-Variance Relation” found that the correlation between the market’s expected return and its conditional volatility is positive during low-sentiment periods and nearly flat during high-sentiment periods. In other words, the market is less rational during high-sentiment periods, due to higher participation by “noise” traders in such periods.

Given that the anomalies the authors examined are well-known (they present challenges to the efficient markets hypothesis), why do they persist?

Limits To Arbitrage

Anomalies can persist when there are limits to arbitrage:

• Many institutional investors, such as pension plans, endowments and mutual funds, are prohibited by their charters from taking short positions.
• Shorting can be expensive—you have to borrow a stock to go short, and many stocks are costly to borrow because the supply available from institutional investors is low.
• Investors are unwilling to accept the risks of shorting because of the potential for unlimited losses. Traders who believe a stock’s price is too high know they can be correct (its price may eventually fall) but still face the risk the price will go up before it goes down. Such a price move, requiring additional capital, can force traders to liquidate at a loss. Long-only investors don’t face this risk. The risk aversion is so high that the study “All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors” found only 0.29% of the positions held by individual investors are short positions.

Because of these impediments to short selling, overpricing becomes more difficult to eliminate. Stambaugh, Yu and Yuan concluded that, given these short-sale impediments, overpricing should be more prevalent than underpricing.

They write: “Investors with the most optimistic views about a stock, relative to the views of other investors, exert the greatest effect on the stock’s price, because their views are not counterbalanced by the valuations of the relatively less optimistic investors. The latter investors are inclined to take no position if they view the stock as undervalued, rather than take a short position. When the most optimistic investors are too optimistic and overvalue the stock, overpricing results. In contrast, underpricing is less likely. As long as the cross section of views includes the view of rational investors, the most optimistic investors do not undervalue the stock.”

A more recent contribution to the literature on investor sentiment comes from Muhammad Cheema, Yimei Man and Kenneth Szulczyk, authors of the April 2018 study “State of Investor Sentiment and Aggregate Stock Market Returns.” The study covered the period July 1965 to October 2015.

They found that the Baker-Wurgler investor sentiment index is a reliable contrarian predictor of subsequent monthly, six- and 12-month market returns, but only during high-sentiment periods. For example, they found that during high-sentiment periods, the return is -0.9% over the subsequent month, -0.8% over the subsequent six months and -0.5% over the subsequent year. Each result was significant at the 1% confidence level. On the other hand, in periods of low sentiment, none of the data was significant.

The authors concluded: “These results are consistent with a setting such as high-sentiment periods where overpricing is more prevalent than underpricing since short-sale restrictions limit the ability of rational investors to exploit overpricing but not underpricing.”

Conclusion

The lesson for investors is to avoid being a noise trader. Don’t get caught up in following the herd over the investment cliff. Stop paying attention to prognostications in the financial media. Most of all, have a well-developed, written investment plan. Develop the discipline to stick to it, rebalancing when needed and harvesting losses as opportunities present themselves.

Larry Swedroe is the director of research for The BAM Alliance, a community of more than 140 independent registered investment advisors throughout the country.