Understanding Systematic Risk: A High‐Frequency Approach

ABSTRACT Based on a novel high‐frequency data set for a large number of firms, I estimate the time‐varying latent continuous and jump factors that explain individual stock returns. The factors are estimated using principal component analysis applied to a local volatility and jump covariance matrix. I find four stable continuous systematic factors, which can be well approximated by a market, oil, finance, and electricity portfolio, while there is only one stable jump market factor. The exposure of stocks to these risk factors and their explained variation is time‐varying. The four continuous factors carry an intraday risk premium that reverses overnight.