On estimating market microstructure noise variance

- Propose modified estimates of market microstructure noise (MMN) variance based on Hansen and Lunde (2006).
- Report Monte Carlo results of comparison of different estimates of MMN variance.
- Report better performance of modified estimates at different frequencies.
- Report empirical estimates of MMN variance for some liquid NYSE stocks in 2010-2013.

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.