高頻財務資料波動性的估計

Estimating Financial Volatility with High Frequency Data

李盈瑩(Ying-Ying Lee)

指導教授 ： 管中閔

國立臺灣大學/管理學院/財務金融學研究所/碩士(2006年)

https://doi.org/10.6342/NTU.2006.00103

摘要

無資料

關鍵字

波動性 ； 高頻資料 ； 市場微結構 ； 台灣證券交易所

並列摘要

The sum of squared returns, or realized volatility, of the recently available high frequency financial data should be a good estimator for integrated volatility. However, the empirical studies suggest that the market microstructure noise which contaminates the efficient prices would make realized volatility inconsistent. We review the recent literature on the estimators for integrated volatility and the market microstructure noise. We focus on the statistical properties and the empirical findings of the subsample-based estimators, e.g., Two Scales Realized Volatility (TSRV), and the kernel-based estimators. Our empirical analysis on the transactions of two actively-traded Taiwan Stock Exchange stocks does not reject the assumption that the market microstructure noise is serially independent and independent of the efficient
price. Our results support that TSRV is practically applicable for computing realized volatility of these two stocks. We also find that the jumps in the efficient prices might not be negligible by bipower variation. We propose a method to estimate the autocorrelation of the noise by the empirical autocorrelation of the log-returns.

並列關鍵字

realized volatility ； realized variance ； high frequency data ； market microstructure ； subsampling ； Taiwan Stock Exchange

參考文獻

Intraday information, trading volume, and return volatility: evidence from the order flows on the Taiwan Stock Exchange,

Ultra high frequency volatility estimation with dependent microstructure noise, Working paper, Princeton University.

Journal of Business and Economics Statistics, 24, 2, 162-167.

The distribution of realized stock return volatility.

Journal of Financial Economics, 61, 43-76.