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Dependent microstructure noise and integrated volatility estimation from high-frequency data
- Source :
- Journal of Econometrics, 215(2), 536-558. Elsevier
- Publication Year :
- 2020
-
Abstract
- In this paper, we develop econometric tools to analyze the integrated volatility of the efficient price and the dynamic properties of microstructure noise in high-frequency data under general dependent noise. We first develop consistent estimators of the variance and autocovariances of noise using a variant of realized volatility. Next, we employ these estimators to adapt the pre-averaging method and derive a consistent estimator of the integrated volatility, which converges stably to a mixed Gaussian distribution at the optimal rate $n^{1/4}$. To refine the finite sample performance, we propose a two-step approach that corrects the finite sample bias, which turns out to be crucial in applications. Our extensive simulation studies demonstrate the excellent performance of our two-step estimators. In an empirical study, we characterize the dependence structures of microstructure noise in several popular sampling schemes and provide intuitive economic interpretations; we also illustrate the importance of accounting for both the serial dependence in noise and the finite sample bias when estimating integrated volatility.
- Subjects :
- Mathematics, Interdisciplinary Applications
Economics and Econometrics
Pre-averaging method
Realized variance
Computer science
Economics
Gaussian
Frequency data
Social Sciences
Mathematics - Statistics Theory
Statistics Theory (math.ST)
EFFICIENT ESTIMATION
symbols.namesake
Dependent microstructure noise
Empirical research
Integrated volatility
PRICES
JUMPS
Business & Economics
BID-ASK SPREAD
FOS: Mathematics
Applied mathematics
REALIZED VARIANCE
Sampling bias
Science & Technology
Applied Mathematics
COMPONENTS
Estimator
Social Sciences, Mathematical Methods
Microstructure
TIME
MARKET
Physical Sciences
symbols
Bias correction
Volatility (finance)
Realized volatility
Mathematics
Mathematical Methods In Social Sciences
Subjects
Details
- Language :
- English
- ISSN :
- 03044076
- Volume :
- 215
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Journal of Econometrics
- Accession number :
- edsair.doi.dedup.....40219d5c5bd9a60b4d5cfbf4028607fe