(MoneyWatch) Many studies have documented long-term historical phenomena in securities markets that contradict the efficient market hypothesis and can't be captured plausibly in models based on perfect investor rationality.
Behavioral finance attempts to fill the void by proposing psychology-based theories to explain market anomalies.
Recently, there have been several papers focusing on what is called "investor sentiment" -- the propensity of individuals to trade on "noise" and emotions rather than facts. Sentiment causes investors to have beliefs about future cash flows and investment risks that aren't justified. Two researchers, Malcolm Baker and Jeffrey Wurgler, have constructed an investor sentiment index based on the six measures:
- Trading volume as measured by New York Stock Exchange turnover
- The dividend premium (the difference between the average market-to-book ratio of dividend payers and non-payers)
- The closed-end fund discount
- The number of IPOs
- The first-day returns on IPOs
- The equity share in new issues
The authors of a October 2011 study were the first to investigate the effect of global and local components of investor sentiment on major stock markets. The researchers -- Malcolm Baker of Harvard University, Jeffrey Wurgler of New York University, and Yu Yuan of the University of Pennsylvania -- looked at sentiment both at the level of the country average and the time series of the cross-section of stock returns. They also studied whether sentiment spreads across markets. The study covered the period from 1980 through 2005 and stock markets in six countries: Canada, France, Germany, Japan, the U.K., and the U.S. They also compiled a global sentiment index, the first of its kind. The following is a summary of their findings:
- Investor sentiment played a significant role in international market volatility and generated return predictability of a form consistent with corrections of overreaction.
- Total sentiment, particularly the global component of total sentiment, was a contrarian predictor of country-level market returns -- high investor sentiment predicted low future returns, and vice versa. The results were similar for both value- and equal-weighted market returns and for non-U.S. markets.
- The economic significance of the effect was nontrivial. A one-standard-deviation increase in a country's total investor sentiment index was associated with 3.5 percent per year lower value-weighted market returns and 4.3 percent per year lower equal-weighted returns.
- The country-level results are mainly driven by global sentiment. A one-standard-deviation increase in the global sentiment index was associated with 5.4 percent per year lower value-weighted market returns and 5.6 percent per year lower equal-weighted market returns.
- Broad waves of sentiment had greater effects on hard-to-arbitrage (due to greater costs and greater risks) and hard-to-value stocks (small, high-return-volatility, growth and distressed stocks). These stocks will exhibit high "sentiment beta."
- Sorting stocks across years according to whether the level of their total sentiment index was positive or negative, the top volatility decile stocks earned 16.1 percent per year lower returns when the year started in a high-sentiment state -- consistent with a correction of sentiment-driven overpricing. High sentiment periods also foreshadowed 1 percent per month lower returns on the smallest capitalization portfolio, another economically large effect. The effect of sentiment was much smaller on low volatility stocks or large stocks as they were relatively easy to arbitrage and value.
- Not only did local and global sentiment predict the cross-section of a country's returns, but investor sentiment was contagious -- U.S. sentiment impacted returns for countries linked with the U.S. by significant capital flows. (This conclusion didn't depend on including the U.S. 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."
These findings help explain the poor performance of individual investors who, on average, are noise chasers. Following the crowd, like sheep to the slaughter, they tend to rush into whatever is the latest new, new thing, be it the "-tronic" era of the 60s, the "nifty-fifty" era of the 70s, the biotech era of the 80s, or the dot-com era of the 90s, driving prices to levels that predict low future returns.
This decade, social media companies are the latest fixation for many investors. The winning strategy is to have a well-developed plan and to stick to it, not allowing investor sentiment to influence your investment decisions.