Market Risk Models for Intraday Data

In this paper, we quantify market risk at an intraday time horizon using normal GARCH, Student GARCH, RiskMetrics and high-frequency duration (Log-ACD) models set in the framework of the conditional VaR methodology. Because of the small time horizon of the intraday returns (15 and 30 minute returns in this paper), an evaluation of intraday market risk can be useful to market participants (traders, market makers) involved in frequent trading. As expected, the volatility features an important intraday seasonality, which must be removed prior to using the market risk models. The four models are applied to intraday returns data for three stocks traded on the New York Stock Exchange and it is shown that the Student GARCH model performs best. We also comment on the use of price durations as a measure of risk on time.