5 - Volatility Modeling Using Intraday Data

Abstract

Realized volatility and range-based volatility are more informative about daily volatility than is the daily squared return. This fact has important implications for the evaluation of volatility forecasts and has even more important implications for volatility forecast construction. If intraday information is available then it is used to construct more accurate volatility forecasts than those that can be constructed from daily returns alone. This chapter introduces a number of practical approaches to volatility forecasting using intraday information. In addition, the construction of the intraday price grid is perhaps the most challenging task when estimating and forecasting volatility using realized variance. The raw intraday price data contains observations randomly spaced in time and the sheer volume of data can be enormous when investigating many assets over long time periods. The construction of the grid of prices is complicated by the presence of data errors. A data error is broadly defined as a quoted price that does not conform to the real situation of the market. Price data errors are of several forms, such as decimal errors.