Abstract: Using an equity mispricing score that incorporates 155 anomaly characteristics, I find that U.S. firms are 59% more likely to issue equity when overvalued and 28% more likely to repurchase shares when undervalued. Moreover, this relationship is more pronounced when executives own more equity in the firm. I also show that executives are more likely to use equity as currency in acquisitions when overvalued and use cash when undervalued. I find consistent evidence using an international dataset that includes 33 countries. These findings provide new evidence about market timing and support the market timing hypothesis.
Presentations: AFA (2023), SFA (2022), FMA (2022), ASU (2021)
Abstract: We examine the impact of monetary policy uncertainty (MPU) in predicting asset price bubbles. Using US data from 1926-2019, we find that greater monetary policy uncertainty leads to a greater likelihood of bubbles in industry level returns. The result is robust to criticisms on the ex-ante identification of bubbles. The evolution of this relationship over time is concomitant with the FED's increased transparency of its monetary policy. Machine learning models that incorporate MPU outperform models that don't in their ability to predict bubbles in real time.