1 Department of Marketing and Statistics, Aarhus School of Business, Aarhus BSS, Aarhus University2 Econometric Modelling, Aarhus School of Business, Aarhus BSS, Aarhus University3 Department of Economics, Stanford University4 Department of Economics and Business Economics, Aarhus BSS, Aarhus University5 Department of Economics and Business Economics, Aarhus BSS, Aarhus University
We study market microstructure noise in high-frequency data and analyze its implications for the realized variance (RV) under a general specification for the noise. We show that kernel-based estimators can unearth important characteristics of market microstructure noise and that a simple kernel-based estimator dominates the RV for the estimation of integrated variance (IV). An empirical analysis of the Dow Jones Industrial Average stocks reveals that market microstructure noise its time-dependent and correlated with increments in the efficient price. This has important implications for volatility estimation based on high-frequency data. Finally, we apply cointegration techniques to decompose transaction prices and bid-ask quotes into an estimate of the efficient price and noise. This framework enables us to study the dynamic effects on transaction prices and quotes caused by changes in the efficient price.
Journal of Business and Economic Statistics, 2006, Vol 24, Issue 2, apr, p. 127-161