I discuss a new intellectual paradigm, social economics and finance —the study of the social processes that shape economic thinking and behavior. This emerging field recognizes that people observe and talk to each other. A key, underexploited building block of social economics and finance is social transmission bias : systematic directional shift in signals or ideas induced by social transactions. I use five “fables” (models) to illustrate the novelty and scope of the transmission bias approach, and offer several emergent themes. For example, social transmission bias compounds recursively, which can help explain booms, bubbles, return anomalies, and swings in economic sentiment.

Identifying firm connections by shared analyst coverage, we find that a connected-firm (CF) momentum factor generates a monthly alpha of 1.68% (t = 9.67). In spanning regressions, the alphas of industry, geographic, customer, customer/supplier industry, single- to multi-segment, and technology momentum factors are insignificant/negative after controlling for CF momentum. Similar results hold in cross-sectional regressions and in developed international markets. Sell-side analysts incorporate news about linked firms sluggishly. These effects are stronger for complex and indirect linkages. Consistent with limited investor attention, these results indicate that momentum spillover effects are a unified phenomenon that is captured by shared analyst coverage.

We propose a theoretically motivated factor model based on investor psychology and assess its ability to explain the cross-section of U.S. equity returns. Our factor model augments the market factor with two factors that capture long- and short-horizon mispricing. The long-horizon factor exploits the information in managers’ decisions to issue or repurchase equity in response to persistent mispricing. The short-horizon earnings surprise factor, which is motivated by investor inattention and evidence of short-horizon underreaction, captures short-horizon anomalies. This 3-factor risk-and-behavioral model outperforms other proposed models in explaining a broad range of return anomalies.

Existing research has found cross-sectional seasonality of stock returns—the periodic outperformance of certain stocks during the same calendar months or weekdays. We hypothesize that assets’ different sensitivities to investor mood explain these effects and imply other seasonalities. Consistent with our hypotheses, relative performance across individual stocks or portfolios during past high or low mood months and weekdays tends to recur in periods with congruent mood and reverse in periods with noncongruent mood. Furthermore, assets with higher sensitivities to aggregate mood—higher mood betas—subsequently earn higher returns during ascending mood periods and earn lower returns during descending mood periods.

We examine the causal effect of limits to arbitrage on 11 well‐known asset pricing anomalies using the pilot program of Regulation SHO, which relaxed short‐sale constraints for a quasi‐random set of pilot stocks, as a natural experiment. We find that the anomalies became weaker on portfolios constructed with pilot stocks during the pilot period. The pilot program reduced the combined anomaly long–short portfolio returns by 72 basis points per month, a difference that survives risk adjustment with standard factor models. The effect comes only from the short legs of the anomaly portfolios.