Separating Microstructure Noise from Volatility
- 19 February 2004
- preprint
- Published by Elsevier in SSRN Electronic Journal
Abstract
There are two volatility components embedded in the returns constructed using recorded stock prices: the genuine time-varying volatility of the unobservable returns that would prevail (in equilibrium) in a frictionless, full-information, economy and the variance of the equally unobservable microstructure noise. Using straightforward sample averages of high-frequency return data recorded at different frequencies, we provide a simple technique to identify both volatility features. We apply our methodology to a sample of S&P100 stocks.Keywords
This publication has 32 references indexed in Scilit:
- Long Memory and the Relation Between Implied and Realized VolatilityJournal of Financial Econometrics, 2006
- How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure NoisePublished by National Bureau of Economic Research ,2003
- Modeling and Forecasting Realized VolatilityEconometrica, 2003
- Parametric and Nonparametric Volatility MeasurementPublished by National Bureau of Economic Research ,2002
- Range‐Based Estimation of Stochastic Volatility ModelsThe Journal of Finance, 2002
- The Distribution of Stock Return VolatilityPublished by National Bureau of Economic Research ,2000
- Intraday periodicity and volatility persistence in financial marketsPublished by Elsevier ,1998
- Deutsche Mark–Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run DependenciesThe Journal of Finance, 1998
- Fractionally integrated generalized autoregressive conditional heteroskedasticityJournal of Econometrics, 1996
- Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency ReturnsPublished by National Bureau of Economic Research ,1996