We survey the textual sentiment literature, comparing and contrasting the various information sources, content analysis methods, and empirical models that have been used to date. We summarize the important and influential findings about how textual sentiment impacts on individual, firm-level and...

In this study we develop a trading strategy that exploits limited investor attention. Trading signals for US S&P 500 stocks are derived from Google Search Volume data, taking a long position if investor attention for the corresponding security was abnormally low in the past week. Our strategy...

We exploit a unique dataset to study how the information sets of retail and institutional investors evolve over time. In line with theoretical models of rational inattention, investors’ information set is related to their sophistication, with more sophisticated investors tracking more stocks....

How might markets exhibit both short-term reversals and longer-term momentum? Motivated by this question, we develop a dynamic model which includes noise traders and investors who underreact to signals that they do not themselves produce. Our setting implies the following: Return predictability...

We identify model-free mispricing factors and relate them to global stock prices and investor beliefs. The factors measure variation in the relative mispricing of closed-end funds and their underlying assets. We design three factors to reflect the beliefs and capital flows of important...

We extend the noise trader risk model of Delong et al. (J Polit Econ 98:703–738, 1990) to a model with multiple risky assets to demonstrate the effect of investor sentiment on the cross-section of stock returns. Our model formally demonstrates that market-wide sentiment leads to relatively...

We use the returns on lottery-like stocks to construct a novel index for investor sentiment in the stock market. This new measure is closely related to previously developed sentiment indicators, but more accurately tracks speculative episodes over the sample period. Using our index, we find that...

Portfolio optimization focuses on risk and return prediction, yet implementation costs critically matter. Predicting trading costs is challenging because costs depend on trade size and trader identity, thus impeding a generic solution. We focus on a component of trading costs that applies...

Using survey-based explicit investor sentiment measures, this paper analyzes when investors' stock market expectations are a ffected by weather-induced mood. This study provides new insights into mood and decision making by directly comparing private and institutional investors. This paper shows...

Using a unique database this study establishes a relationship between firm-specific investor sentiment and stock price movements around earnings announcements. We find that firm-specific investor sentiment is a key determinant of price adjustment in the context of an earnings surprise....