Can crowdsourced data help investors take better decisions? This paper1 finds outperformance for firms that experience improvements in crowdsourced employer ratings. The sample used is based on over a million employee-level company reviews for more than a thousand firms obtained from Glassdoor, an employer review website, over the 2008-2016 period.
Decomposing employer ratings, the authors find that the return effect is related to changing employee assessments of career opportunities and views of senior management, but not to work-life balance. They conclude that employee reviews reveal information about the firm that is not yet reflected in stock prices.
We consider this paper to be a nice example of how big data may be used to enhance traditional quantitative investment strategies. As with many of these studies, however, some words of caution are also in place: the sample is relatively short, covering barely one economic cycle, and therefore also the statistical significance of the results is weak. Moreover, the required data is not easy to obtain and only covers a limited number of stocks. Nevertheless, big data in general has a lot of potential and is a topic that is also high on our research agenda.
1 Green, Huang, Wen & Zhou, “Crowdsourced Employer Reviews and Stock Returns”, SSRN working paper, no. 3002707, 2017.
Nuestros investigadores publican multitud de informes basados en sus propios estudios empíricos; también siguen los análisis cuantitativos que hacen los demás. Comentarios de nuestro responsable de análisis cuantitativo para renta variable, David Blitz, sobre publicaciones externas de gran relevancia.