Change-points and functional features of intraday volatility in China stock market

Realized volatility models are enhanced in this paper through the use of change-point detection and functional regression. We explore the time-varying intraday features of realized volatility in the morning and afternoon sessions in China’s stock market. The empirical results reveal significant structural discontinuities in the realized volatility generated from high-frequency data in China’s stock market: the coefficients of AR term and realized quarticity (RQ) term vary with time in the day and experience different patterns. From two perspectives—information digestion and investor behavior—we examine how coefficients of the AR term and RQ term change over trading time with different levels of volatility.