Abstract:

Modern asset pricing theory predicts an unambiguously positive relationship between volatility and expected returns. Empirically, however, realized volatility in the past often predicts expected returns in the future with a negative sign, as exemplified by the volatility-managed portfolios of Moreira and Muir (2017). Theoretically, we show that information-driven volatility induces a negative correlation between past realized volatility and expected volatility and expected returns in the future. We develop a simple asset pricing model based on this intuition and demonstrate that our model can account for several volatility-related asset pricing puzzles such as the return on volatility managed portfolios, the “variance risk premium” return predictability (Bollerslev, Tauchen, and Zhou, 2009), and the predictability of returns by implied volatility reduction on macroeconomic announcement days.

主讲人介绍：

Hengjie Ai, Professor of Finance and Robert M. Steiner Chair in Business at the University of Wisconsin-Madison. Prior to joining the Wisconsin School of Business, Professor Ai served as a faculty member in Finance at the Carlson School of Management at the University of Minnesota. Professor Ai’s research interests include topics in asset pricing, corporate finance, and macroeconomic theory. His research has been published in top Economics journals such as Econometrica, and top finance journals such as the Journal of Finance, the Journal of Financial Economics, and the Review of Financial Studies.