A Semiparametric Intraday GARCH Model

59 Pages Posted: 28 May 2016

See all articles by Peter Malec

Peter Malec

University of Cambridge - Faculty of Economics

Date Written: May 27, 2016

Abstract

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

JEL Classification: C14, C22, C53 , C58

Suggested Citation

Malec, Peter, A Semiparametric Intraday GARCH Model (May 27, 2016). Available at SSRN: https://ssrn.com/abstract=2785615 or http://dx.doi.org/10.2139/ssrn.2785615

Peter Malec (Contact Author)

University of Cambridge - Faculty of Economics ( email )

Sidgwick Avenue
Cambridge, CB3 9DD
United Kingdom

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