In a recently published paper, Edmans, García, and Norli (2007) reveal a strong association between results of soccer games and local stock returns. Inspired by their work, we propose a novel approach to exploit this effect on the aggregate international level with the following three unique features: i) The aggregate effect does not depend on the games’ results; hence, the effect is an exploitable predictable effect. ii) The aggregate effect is based on many games; hence, it is very large and highly significant. We find that the average return on the U.S. market over the World Cup’s effect period is – 2.58%, compared to +1.21% for all-days average returns over the same period length. iii) Exploiting the aggregate effect is involved with trading in a single index for a relatively long period.

This paper examines the intertemporal relation between downside risk and expected stock returns. Value at Risk (VaR), expected shortfall, and tail risk are used as measures of downside risk to determine the existence and significance of a risk-return tradeoff. We find a positive and significant relation between downside risk and the portfolio returns on NYSE/AMEX/Nasdaq stocks. VaR remains a superior measure of risk when compared with the traditional risk measures. These results are robust across different stock market indices, different measures of downside risk, loss probability levels, and after controlling for macroeconomic variables and volatility over different holding periods as originally proposed by Harrison and Zhang (1999).

Behavioral economic studies reveal that negative sentiment driven by bad mood and anxiety affects investment decisions and may hence affect asset pricing. In this study we examine the effect of aviation disasters on stock prices. We find evidence of a significant negative event effect with an average market loss of more than 60 billion per aviation disaster, whereas the estimated actual loss is no more than 1 billion. In two days a price reversal occurs. We find the effect to be greater in small and riskier stocks and in firms belonging to less stable industries. This event effect is also accompanied by an increase in the perceived risk: implied volatility increases after aviation disasters without an increase in actual volatility.

This paper provides new evidence on the time-series predictability of stock market returns by introducing a test of nonlinear mean reversion. The performance of extreme daily returns is evaluated in terms of their power to predict short- and long-horizon returns on various stock market indices and size portfolios. The paper shows that the speed of mean reversion is significantly higher during the large falls of the market. The parameter estimates indicate a negative and significant relation between the monthly portfolio returns and the extreme daily returns observed over the past one to eight months. Specifically, in a quarter in which the minimum daily return is −2% the expected excess return is 37 basis points higher than in a month in which the minimum return is only −1%. This result holds for the value-weighted and equal-weighted stock market indices and for each of the size decile portfolios. The findings are also robust to different sample periods, different indices, and investment horizons.

Do happy people predict future risk and return differently from unhappy people, or do individuals rely only on economic facts? We survey investors on their subjective sentiment-creating factors, return and risk expectations, and investment plans. We find that noneconomic factors systematically affect return and risk expectations, where the return effect is more profound. Investment plans are also affected by noneconomic factors. Sports results and general feelings significantly affect predictions. Sufferers from seasonal affective disorder have lower return expectations in the autumn than in other seasons, supporting the winter blues hypothesis.