General Bayesian time?varying parameter vector autoregressions for modeling government bond yields

Forecasting government bond yields with large Bayesian vector autoregressions

We propose a new approach to forecasting the term structure of interest rates, which allows to efficiently extract the information contained in a large panel of yields. In particular, we use a large Bayesian Vector Autoregression (BVAR) with an optimal amount of shrinkage towards univariate AR models. The optimal shrinkage is chosen by maximizing the Marginal Likelihood of the model. Focusing o...

Bayesian Vector Autoregressions

This article provides an introduction to the burgeoning academic literature on Bayesian Vector Autoregressions, benchmark models for applied macroeconomic research. We first explain Bayes’ theorem and the derivation of the closed-form solution for the posterior distribution of the parameters of the model given data. We further consider parameter shrinkage, a distinguishing feature of the prior ...

How Does Liquidity Affect Government Bond Yields?∗

The paper explores the determinants of yield differentials between sovereign bonds, using Euro area data. There is a common trend in yield differentials, which is correlated with a measure of aggregate risk. In contrast, liquidity differentials display sizeable heterogeneity and no common factor. We propose a simple model with endogenous liquidity demand, where a bond’s liquidity premium depend...

Order determination in general vector autoregressions

Abstract: In the application of autoregressive models the order of the model is often estimated using either a sequence of likelihood ratio tests, a likelihood based information criterion, or a residual based test. The properties of such procedures has been discussed extensively under the assumption that the characteristic roots of the autoregression are stationary. While non-stationary situati...

Macroeconomic Modeling with Asymmetric Vector Autoregressions