A Semiparametric Intraday GARCH Model
Monday 30th May 2016
CINET:
1606
Malec, P.
We propose a multiplicative component model for intraday volatility. The model consists
of a seasonality factor, as well as a semiparametric and parametric component. The
former captures the well-documented intraday seasonality of volatility, while the latter
two account for the impact of the state of the limit order book, utilizing an additive
structure, and fluctuations around this state by means of a unit GARCH specification.
The model is estimated by a simple and easy-to-implement approach, consisting of
across-day-averaging, smooth-backfitting and QML steps. We derive the asymptotic
properties of the three component estimators. Further, our empirical application
based on high-frequency data for NASDAQ equities investigates non-linearities in
the relationship between the limit order book and subsequent return volatility and
underlines the usefulness of including order book variables for out-of-sample forecasting
performance.
Keywords
Intraday volatility
GARCH
smooth backfitting
additive models
limit
order book
C14
C22
C53
C58
Themes
empirical