We study the market microstructure noise-variance estimation of high-frequency stock prices. Based on the Hansen and Lunde (2006) approach, we propose estimates using subsampling method at different time scales. We conduct a Monte Carlo study to compare our method against others in the literature. Our results show that our proposed estimates have lower (absolute) mean error and root mean-squared error, and their performance is quite stable at different time scales.
High-frequency data, Microstructure noise, Noise-to-signal ratio, Realized variance
Econometrics | Economic Theory
DONG, Yingjie and TSE, Yiu Kuen.
On estimating market microstructure noise variance. (2017). Economics Letters. 150, 59-62. Research Collection School Of Economics.
Available at: https://ink.library.smu.edu.sg/soe_research/1921