Dynamic Bayesian Predictive Synthesis in Time Series Forecasting [article]

Kenichiro McAlinn, Mike West
2017 arXiv   pre-print
We discuss model and forecast combination in time series forecasting. A foundational Bayesian perspective based on agent opinion analysis theory defines a new framework for density forecast combination, and encompasses several existing forecast pooling methods. We develop a novel class of dynamic latent factor models for time series forecast synthesis; simulation-based computation enables implementation. These models can dynamically adapt to time-varying biases, miscalibration and
more » ... cies among multiple models or forecasters. A macroeconomic forecasting study highlights the dynamic relationships among synthesized forecast densities, as well as the potential for improved forecast accuracy at multiple horizons.
arXiv:1601.07463v5 fatcat:albd4eqrtzfwbkmtpja53o7jbm