Weighted Realized Beta and Its Application in Chinese Stock Market
In recent years, research on high frequency data has been a new research field in financial econometrics. In this paper, we put forward weighted realized beta to estimate the beta by using high-frequency data. By using high-frequency data, we can fully take advantage of the intraday information of the stock market. We cast our analysis of weighted realized beta within the framework of weighted realized variance and weighted realized covariance. Weighted realized variance and weighted realized covariance are unbiased estimators of variance and covariance with the least variance based on high frequency data. Our approach makes the beta observable and model-free. Our empirical analysis is based on high frequency data from the Chinese stock market- -Shenzhen stock market. We further explore the dynamic nature of weighted realized beta. Through the empirical analysis, we indicate that the weighted realized beta of the stock listed in Shenzhen stock market is time-varying and persistent.
Weighted Realized Variance Weighted Realized Covariance Weighted Realized Beta Long Memory
Guo Mingyuan Zhang Shiying Huo Guangyao
School of Management, Tianjin University, Tianjin P.R.China, 300072 Tianjin Institute of Urban Construction, Tianjin P.R.China, 300384
国际会议
天津
英文
2007-10-20（万方平台首次上网日期，不代表论文的发表时间）