Realized volatility forecasting and market microstructure noise

Torben G. Andersen, Tim Bollerslev, Nour Meddahi

Research output: Contribution to journalArticlepeer-review

84 Scopus citations

Abstract

We extend the analytical results for reduced form realized volatility based forecasting in ABM (2004) to allow for market microstructure frictions in the observed high-frequency returns. Our results build on the eigenfunction representation of the general stochastic volatility class of models developed byMeddahi (2001). In addition to traditional realized volatility measures and the role of the underlying sampling frequencies, we also explore the forecasting performance of several alternative volatility measures designed to mitigate the impact of the microstructure noise. Our analysis is facilitated by a simple unified quadratic form representation for all these estimators. Our results suggest that the detrimental impact of the noise on forecast accuracy can be substantial. Moreover, the linear forecasts based on a simple-to-implement 'average' (or 'subsampled') estimator obtained by averaging standard sparsely sampled realized volatility measures generally perform on par with the best alternative robust measures.

Original languageEnglish (US)
Pages (from-to)220-234
Number of pages15
JournalJournal of Econometrics
Volume160
Issue number1
DOIs
StatePublished - Jan 1 2011

Keywords

  • Eigenfunction stochastic volatility models
  • High-frequency data
  • Integrated volatility
  • Market microstructure noise
  • Realized volatility
  • Robust volatility measures
  • Volatility forecasting

ASJC Scopus subject areas

  • Economics and Econometrics

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