| 主讲人简介： | Jia Chen is a Professor of Economics from Department of Economics at University of York, UK. Her research interests are mainly in panel data econometrics and time series econometrics, in particular, nonparametric and semiparametric modelling, which involves development of statistical models, estimation, hypothesis testing, and model selection approaches. Her research has been published in international journals such as Annals of Statistics, Journal of Business and Economic Statistics, Journal of Econometrics, Econometrics Journal, among others. |
| 讲座简介： | We develop the Double Principal Component Analysis (DPCA) based on a dual factor structure for high-frequency intraday returns contaminated by microstructure noise. The dual factor structure allows a factor structure for microstructure noise in addition to the factor structure for the efficient log-prices. We construct estimators of factors for both the efficient log-prices and the microstructure noise as well as their common components, and prove the 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. |
