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dc.contributor.authorLi, Y-N.
dc.contributor.authorChen, J.
dc.contributor.authorLinton, O.
dc.date.accessioned2022-01-06T10:45:28Z
dc.date.available2022-01-06T10:45:28Z
dc.date.issued2021-06-30
dc.identifier.otherCWPE2150
dc.identifier.otherC-INET2122
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/332141
dc.description.abstractWe develop the Double Principal Component Analysis (DPCA) based on a dual factor structure for high-frequency intraday returns data contaminated with microstructure noise. The dual factor structure allows a factor structure for the microstructure noise in addition to the factor structure for efficient log-prices. We construct estimators of factors for both efficient log-prices and microstructure noise as well as their common components, and provide uniform consistency of these estimators when the number of assets and the sampling frequency go to infinity. In a Monte Carlo exercise, we compare our DPCA method to a PCA-VECM method. Finally, an empirical analysis of intraday returns of S&P 500 Index constituents provides evidence of co-movement of the microstructure noise that distinguishes from latent systematic risk factors.
dc.publisherFaculty of Economics, University of Cambridge
dc.relation.ispartofseriesCambridge Working Papers in Economics
dc.relation.ispartofseriesCambridge-INET Working Paper Series
dc.rightsAll Rights Reserved
dc.rights.urihttps://www.rioxx.net/licenses/all-rights-reserved/
dc.subjectCointegration
dc.subjectFactor model
dc.subjectHigh-frequency data
dc.subjectMicrostructure noise
dc.subjectNon-stationarity
dc.titleEstimation of Common Factors for Microstructure Noise and Efficient Price in a High-frequency Dual Factor Model
dc.typeWorking Paper
dc.identifier.doi10.17863/CAM.79587
datacite.isnewversionof.doi10.17863/CAM.74486


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