5. Volatility Modeling Using Intraday Data
This chapter explores the use of intraday prices for computing daily volatility and for forecasting future volatility. We first introduce the concept of realized variance (RV) and look at four stylized facts of RV. We then look at different ways to forecast realized variance, as well as different ways to estimate realized variance, and we briefly look at some of the challenges of working with large and messy intraday data sets. At the end of the chapter we consider range-based proxies of daily volatility and also volatility forecast evaluation using RV and range-based volatility. Range-based volatilities are much easier to construct than RVs but in highly liquid markets RV will be more precise.
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