Unified discrete-time and continuous-time models and statistical inferences for merged low-frequency and high-frequency financial data

作者：Kim, Donggyu; Wang, Yazhen^*

来源：Journal of Econometrics, 2016, 194(2): 220-230.

DOI：10.1016/j.jeconom.2016.05.003

• GARCH
• Ito process
• Quasi-maximum likelihood estimator
• Realized volatility
• Stochastic differential equation

This paper introduces a unified model, which can accommodate both continuous-time Ito processes used to model high-frequency stock prices and GARCH processes employed to model low-frequency stock prices, by embedding a discrete-time GARCH volatility in its continuous-time instantaneous volatility. This model is called a unified GARCH-Ito model. We adopt realized volatility estimators based on high frequency financial data and the quasi-likelihood function for the low-frequency GARCH structure to develop parameter estimation methods for the combined high-frequency and low-frequency data. We establish asymptotic theory for the proposed estimators and conduct a simulation study to check finite sample performances of the estimators. We apply the proposed estimation approach to Bank of America stock price data.

• 出版日期2016-10
• 单位上海财经大学