TITLE:
Bayesian Factorized Cointegration Analysis
AUTHORS:
Kai Cui, Wenshan Cui
KEYWORDS:
Cointegration; Bayesian; Dynamic Factor; Non-Stationary; Root Structure; MCMC
JOURNAL NAME:
Open Journal of Statistics,
Vol.2 No.5,
December
19,
2012
ABSTRACT: The concept of cointegration is widely used in applied non-stationary time series analysis to describe the co-movement of data measured over time. In this paper, we proposed a Bayesian model for cointegration test and analysis, based on the dynamic latent factor framework. Efficient computational algorithms are also developed based on Markov Chain Monte Carlo (MCMC). Performance and efficiency of the the model and approaches are assessed by simulated and real data analysis.