We develop novel multivariate state-space models wherein the latent states evolve on the Stiefel manifold and follow a conditional matrix Langevin distribution. The latent states correspond to time-varying reduced rank parameter matrices, like the loadings in dynamic factor models and the parameters of cointegrating relations in vector error-correction models. The corresponding nonlinear filtering algorithms are developed and evaluated by means of simulation experiments.
Dr. Yang received his PhD degree in 2012 at CREATES, Department of Economics and Business, Aarhus University, Denmark, with the thesis "Modelling Nonlinear Vector Economic Time Series". He also holds a Cand. Polit. from Department of Economics, University of Copenhagen, Denmark, and a B.Eng. in Computer Science and Technology from Shanghai Jiao Tong University, China. He is currently working as a Senior Lecturer at the Department of Statistics, Uppsala University. His research interests include smooth transition models, state-space models, macroeconometrics, financial econometrics, high-dimensional analysis, cointegration, long memory, panel data analysis, directional statistics, Bayesian, MCMC and related computational methods.