Overnight GARCH-Itô Volatility Models

Donggyu Kim, Minseok Shin and Yazhen Wang

Journal of Business & Economic Statistics, 2023, vol. 41, issue 4, 1215-1227

Abstract: 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.

Date: 2023
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DOI: 10.1080/07350015.2022.2116027

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