eThesis - School of Business electronic theses

Understanding who the smart investors are and how they achieve their returns has been an intriguing question to academics and practitioners alike. Having access to smart investors' trades would open perspectives on how the markets work, and what are driving their returns.

For understandable reasons such trade-level access has been rare especially for data on institutional trading. This paper aims to fill a gap in the existing literature by analyzing the institutions' trading behavior using the Ancerno data that provides trade-level visibility on institutions' trades.

This thesis contributes to the existing literature in three key ways. Firstly, it is shown how good performance tends to be persistent for institutions. Secondly, the paper provides evidence that nearly all institutions tend to trade at least some anomalies. Lastly, a link between investor sophistication and the ability to predict market movements is established. Granger causality is used to find that smart institutions also tend to lead their less sophisticated peers in e.g. factor exposures more than vice versa.