Rebuild Normality in Chinese Financial Markets with Range-Based Bipower Variance

Abstract

Realized range and bipower variance are two important improvements for increasingly popular high-frequency realized estimators in financial markets. This paper verifies a new type of estimator named realized range-based bipower variance and carries out its empirical research with high frequency data from Shanghai Composite Index (SHCI) and Shenzhen Synthesis Index (SZSI). The results show that 1) this estimator combines merits of bothrealized range and realized bipower variance. It is as efficient as realized range estimator and at the same timeremains a consistent estimation of integrated variance of Chinese financial markets’ fluctuation; 2) After standardized by realized range based bipower variance, the distributions of SHCI and SZSI’s daily returns are neither skew nor with high kurtos is anymore. The fact tail and high peak of daily returns are basically eliminated by this high-frequency variance estimator, and the standardized distributions of these returns are nearly normal. 3) Comparative studies show that among four types of realized volatility estimators, the range based bipower variance is the best one to rebuild normality in Chinese financial markets. These findings mean when measuring volatility or fluctuations of financial assets, the usage of this new estimator will increase the performance of many financial practices like pricing or risk management. One feasible way to extend this paper is to consider co-estimators of related assets and detect their impacts to the dynamics of volatilities.