We study a dynamic mean-variance portfolio optimization problem under the reinforcement learning framework, where an entropy regularizer is introduced to induce exploration. Due to the time-inconsistency involved in a mean-variance criterion, we aim to learn an equilibrium strategy. Under an...

We identify analysts' information acquisition patterns by linking EDGAR server activity to analysts' brokerage houses. Analysts rely on EDGAR in 26% of their estimate updates with an average of eight filings viewed. We document that analysts' attention to public information is driven by the...

This paper studies how investors react to public messages that may be optimistically biased. We first construct a communication game between an investor and a (possibly) biased securities analyst. We find an equilibrium characterised by the following properties: first, the investor reacts more...

We examine how professional traders behave in two financial market experiments; we contrast professional traders' behavior to that of undergraduate students, the typical experimental subject pool. In our first experiment, both sets of participants trade an asset over multiple periods after...

Earning forecasts disclosed by financial analysts are known to be overly optimistic. Since an investor relies on their expertise, the question arises whether he would take analyst recommendations at face value or instead structure consultation with differently upward-biased analysts in a way...