Overnight GARCH-Itô Volatility Models

Bibliographic Data

ID19420219
AuthorsDonggyu Kim (0000-0002-9226-7065, College of Business, Korea Advanced Institute of Science and Technology (KAIST), Seoul, Korea), Minseok Shin (College of Business, Korea Advanced Institute of Science and Technology (KAIST), Seoul, Korea, corresponding author), Yazhen Wang (0009-0006-9645-4446, University of Wisconsin–Madison)
Year2023
Volume41
Issue4
Pages1215-1227
Publication date2023-10-02
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournal of Business and Economic Statistics (JOURNAL)
Journal identifiersISSN: 0735-0015 • E-ISSN: 1537-2707
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/07350015.2022.2116027
OpenAlexW3159295597
LanguageDE
References cited47

Various parametric volatility models for financial data have been developed to incorporate high-frequency realized volatilities and better capture market dynamics. However, because high-frequency trading data are not available during the close-to-open period, the volatility models often ignore volatility information over the close-to-open period and thus may suffer from loss of important information relevant to market dynamics. In this article, to account for whole-day market dynamics, we propose an overnight volatility model based on Itô diffusions to accommodate two different instantaneous volatility processes for the open-to-close and close-to-open periods. We develop a weighted least squares method to estimate model parameters for two different periods and investigate its asymptotic properties

Autoregressive conditional heteroskedasticity · Econometrics · Economics · Forward volatility · Implied volatility · Realized variance · Stochastic volatility · Volatility smile · Volatility swap · Complex Systems and Time Series Analysis · Financial Risk and Volatility Modeling · Market Dynamics and Volatility

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