A0490
Title: Estimation of common factors for microstructure noise and efficient price in a high-frequency dual-factor model
Authors: Yuning Li - University of York (United Kingdom) [presenting]
Abstract: The Double Principal Component Analysis (DPCA) is developed 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 and their common components. We 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.
