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A Semiparametric Intraday GARCH Model

Peter Malec ()

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

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. (search for similar items in EconPapers)
JEL-codes: C14 C22 C53 C58 (search for similar items in EconPapers)
Date: 2016-05-30
New Economics Papers: this item is included in nep-ets, nep-mst and nep-ore
Note: pm563
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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