A high-frequency test of the risk-return trade-off on macroeconomic announcement days

We demonstrate that high-frequency financial data can be effectively utilized to estimate exposure to common market risk factors and track the dynamics of these exposures following market events, regardless of the presence of market microstructure noise. Using minute-by-minute intraday stock returns spanning the past two decades for the DJIA and S&P 100 index constituents, our findings show that on announcement days, market betas or realized variance of portfolios exhibit a distinctive positive correlation with average excess returns, but this correlation disappears on days without news. The same result holds for intraday betas with data sampled from before-announcement and after-announcement periods, as well as for daily betas or realized variance conditioned on the day type. Additionally, we demonstrate that the behavior of the risk-return trade-off on different trading days paves the way for designing innovative high-frequency trading strategies.