Modeling Overnight and Intraday Volatility with GARCH-Itô Processes

Summary

The paper addresses a gap in volatility modeling: intraday high-frequency data are unavailable between market close and the next open, so models may omit important overnight dynamics. It proposes a GARCH-Itô framework that represents open-to-close and close-to-open periods with distinct instantaneous volatility processes, incorporating both parts of the trading day.

The authors estimate parameters for the two periods using weighted least squares and examine the method’s asymptotic properties. They report a simulation study to assess finite-sample behavior and apply the approach to real trading data. The provided description does not specify the assets, empirical estimates, or comparative performance against alternative models, so it does not establish how much the framework improves forecasts in practice. Its contribution is a modeling and estimation approach designed to retain overnight volatility information alongside intraday dynamics.

Key ideas

• The model separates open-to-close and close-to-open volatility processes.
• Weighted least squares is used to estimate parameters for the two periods.
• The study examines asymptotic properties, simulations, and real trading data.
• The description does not report specific empirical outcomes or comparative forecast gains.

Tags

# Overnight GARCH-Itô Volatility Models


# Overnight GARCH-Itô Volatility Models









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 paper, 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. We conduct a simulation study to check the finite sample performance of the proposed model and method. Finally, we apply the proposed approaches to real trading data.

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