Department of Management

Realized Variance and Market Microstructure Noise

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  • Peter R. Hansen, Stanford University, United States
  • Asger Lunde
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.
Original languageEnglish
JournalJournal of Business and Economic Statistics
Issue2, apr
Pages (from-to)127-161
Publication statusPublished - 2006

    Research areas

  • Integrated variance, Market microstructure noise, Realized variance, Realized volatility, Sampling schemes

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