Various mood-related factors may influence individual investors’ expected month-ahead return forecasts and year-ahead risk forecasts. The authors test likely factors—such as general optimism, seasonality, day of the week, weather, and sports team performance—on risk and return forecasts and find that many factors show strong explanatory power.
The authors augment existing studies that link aggregate sentiment to stock market expectations by examining how individuals who actually invest in stocks forecast risk and return in light of various sentiment-related factors, including each individual’s general mood. The results confirm a significant and persistent influence on participants’ expectations and investment plans, with the greatest impact being on return. In addition, the authors examine the impact of Seasonal Affective Disorder (SAD), favorite sports team performance, and general disposition on the results.
How Is This Research Useful to Practitioners?
Professionals working with individual clients should know as much as possible about what influences clients’ choices and preferences, especially because abundant behavioral research describes how investors do not follow strictly rational processes. The authors define investor sentiment as expectations that do not line up with relevant information, and they proceed to identify mood-related factors that could lead to higher return and lower risk expectations among test subjects. Importantly, they select investors who actually trade in stocks to ensure that the results do not simply reflect a thought experiment.
Consistent with prior research on the topic, several factors seem significantly related to individual investors’ return expectations. In particular, an individual’s general mood and recent favorite sports team performance correlate positively with higher return forecasts. SAD sufferers forecast lower returns in the autumn than in other seasons. Additionally, a combined index of factors significantly affects expected returns. The authors find the impact on returns surprisingly intense and robust to various control factors. (The influence of these factors on risk estimates is not generally significant.)
How Did the Authors Conduct This Research?
Surveys from nearly 600 investors living in the Netherlands addressed sentiment-related factors and market expectations for both Dutch and US stocks. Survey timing helped control for day-of-the-week effects, contemporaneous market sentiment, perception of weather, and season. Responses also identified participants’ general tendency toward optimism or pessimism and helped to control for certain demographic traits. The authors use location-scale ordered probit regressions to first test a factor’s influence on mood and then test how it affects market forecasts individually and as a combined Individual Sentiment Index (ISI). Their hypotheses (quoted from the study) are as follows:
- H1: The better the individual’s general feeling, the higher the expected return.
- H2: The better the individual’s perceived weather, the higher the expected return.
- H3: Stock market return expectations reported by SAD sufferers in the autumn are lower than their own expectations reported in the winter and in the spring or summer.
- H4: The better the individual’s favorite sports team’s result, the higher the expected return.
- H5: Individual mood (general feeling) on weekdays is lower than on weekends, which, in turn, negatively affects return expectations.
- H6: The larger the ISI, the higher (lower) the expected return (volatility).
- H7: The larger the ISI, the higher the individual’s tendency to buy rather than to sell stocks.
Although the authors report more than 1,400 total surveys, fewer than 400 participants returned all three surveys. In addition, forecasts primarily deal with month-ahead market expectations. It might be interesting to see how results differ for longer forecast periods.
The results confirm intuition, although their strength and persistence appear remarkable. This fact should inform other studies as well as guide professionals working with individual investors. The literature has demonstrated many times that individual investor behavior can be irrational. But one must also bear in mind how large numbers of divergent views tend to average out. Given the fact that not all investors share the same perceptions and given the reality that well-informed large traders may trade opposite of common sentiment, professionals should take care not to extend the findings too quickly to explain aggregate market behavior.