Face Value: Trait Impressions, Performance Characteristics, and Market Outcomes for Financial Analysts

Abstract

Using machine learning-based algorithms, we extract key impressions about personality traits from the LinkedIn profile photos of sell-side analysts. We find that these face-based factors are associated with analyst behavior, performance, and capital- and labor-market outcomes. The trustworthiness (TRUST) and dominance (DOM) factors are positively associated with analyst forecast accuracy and report length. Analysts with high TRUST scores tend to herd with managerial guidance forecasts; those with high DOM scores actively participate in conference calls. The positive association of the attractiveness (ATTRACT) factor on forecast accuracy diminishes with market learning and after Reg-FD. Forecasts from analysts with higher TRUST and DOM scores generate stronger price reactions. High DOM scores help male analysts but hurt female analysts to attain All-Star status. These findings suggest that impressions formed from observing analysts’ physical facial attributes are associated with analysts’ economic behaviors. Some of the investor and peer responses to these impressions seem to reflect societal biases and gender stereotypes.