The annual conference starts today and has a strong program. This year's program is very diverse and includes contributions in the estimation of asset pricing models, inference from options, high-dimensional modeling and, of course, estimating components of quadratic variation using high-frequency data.
Which risks matter?
While it is difficult to choose a single paper that I am looking forward to hearing about, "Asset pricing in the frequency domain: theory and empirics" by Ian Dew-Becker and Stefano Giglio caught my eye. This paper uses subtle but important differences in the frequencies that matter for risk -- for example when the utility function in Epstein-Zinn, the low-frequency components of risk are the most important -- to `provide new insights into which models are more compatible asset prices. This is an important areas since many modern models -- habit formation, long-run-risk, or preferences for robustness against the unknown (Hansen-Sargent robust control or other forms of ambiguity aversion) -- can match a large number of common measures of asset prices such as the mean, volatility and persistence of asset prices. This contributes to a rapidly expanding literature that low-frequency features, such as the volatility over the past few years, are more useful for understanding expected returns than higher-frequency components, and is interesting since it substantially challenges the common perception that risk is dominated by surprises.