Autoregression with Non-Gaussian Innovations
Yuzhi Cai · Journal of Time Series Econometrics · 2009
Many economics and finance time series are non-Gaussian. In this paper, we propose a Bayesian approach to non-Gaussian autoregressive time series models via quantile functions. This approach is parametric, so we also compare the proposed parametric approach with a semi-parametric approach. Simulation studies and applications to real time series show that this method works very well.