Finance Associate Professor Hengjie Ai won the Best Paper in Asset Pricing at the Society for Financial Studies (SFS) Cavalcade.

The SFS Cavalcade, which took place May 15 to 18 at Vanderbilt University in Nashville, Tennessee, is a conference dedicated to all things finance.

Ai’s paper, “Risk Preferences and the Macro Announcement Premium,” was co-authored with Ravi Bansal of Duke University. Macro announcements, such as the release of the employment report and the Federal Open Market Committee (FOMC) statements, resolve uncertainty about the future course of the macroeconomy and asset prices react to these announcements instantaneously. A large fraction of the market equity premium is realized within a small number of trading days with significant macroeconomic announcements.

During 1961 to 2014, the cumulative excess returns of the S&P 500 index on the 30 days per year with significant macroeconomic news announcements averaged 3.36 percent, which accounts for 55 percent of the total annual equity premium during this period. The average return on days with macroeconomic announcements is 11.2 basis points (bps), which is significantly higher than the 1.27 bps average return on non-announcement days. High-frequency-data-based evidence shows that much of this premium is realized within hourly windows around announcements, or in a few trading hours prior to the pre-scheduled announcements in the case of the FOMC announcement.

Ai’s paper develops an asset pricing theory that accounts for the announcement premium in the data. He demonstrates that the traditional expected utility analysis is inconsistent with the announcement premium, and new asset pricing models that incorporate generalized risk sensitivity are necessary to explain the pattern of equity market premium in the data.