Towards a unified framework for high and low frequency return volatility modeling

This paper provides a selective summary of recent work that has documented the usefulness of high-frequency, intraday return series in exploring issues related to the more commonly studied daily or lower-frequency returns. We show that careful modeling of intraday data helps resolve puzzles and shed light on controversies in the extant volatility literature that are difficult to address with daily data. Among other things, we provide evidence on the interaction between market microstructure features in the data and the prevalence of strong volatility persistence, the source of significant day-of-the-week effect in daily returns, the apparent poor forecast performance of daily volatility models, and the origin of long-memory characteristics in daily return volatility series.