Overnight GARCH-It\^o Volatility Models
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 paper, to account for whole-day market dynamics, we propose an overnight volatility model based on It\^o 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.
Keywords
Cite
@article{arxiv.2102.13467,
title = {Overnight GARCH-It\^o Volatility Models},
author = {Donggyu Kim and Minseok Shin and Yazhen Wang},
journal= {arXiv preprint arXiv:2102.13467},
year = {2022}
}