2021/02/24 by Donggyu Kim, Kim, Donggyu, Shin, Minseok +1
Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #Econometrics (econ.EM) #FOS: Computer and information sciences #FOS: Economics and business #Financial Risk and Volatility Modeling #Methodology (stat.ME) #Statistical Finance (q-fin.ST) #Stochastic processes and financial applications
paper · pdf · doi:10.48550/arxiv.2102.13467
openalex publication_date 2021/02/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.