Chapter 4 - Bayesian nonparametric methods for financial and macroeconomic time series analysis

Abstract

In this chapter we discuss the use of Bayesian nonparametric methods for time series analysis. First developed by [20] these methods focus on how a stochastic process can be used as a prior over probability measures as well as a prior on the underlining mixing measure in a mixture model. The empirical examples of the chapter centre on financial and macroeconomic time series, and demonstrate that volatility, long-memory and vector autoregressive models underpinned by Bayesian nonparametric methods have superior out-of-sample predictive performance compared to other competitive models.