Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Bayesian Time-Varying Autoregressive Model for Improved Short- and
  Long-Term Prediction   Motivated by the application to German interest rates, we propose a
timevarying autoregressive model for short and long term prediction of time
series that exhibit a temporary non-stationary behavior but are assumed to mean
revert in the long run. We use a Bayesian formulation to incorporate prior
assumptions on the mean reverting process in the model and thereby regularize
predictions in the far future. We use MCMC-based inference by deriving relevant
full conditional distributions and employ a Metropolis-Hastings within Gibbs
Sampler approach to sample from the posterior (predictive) distribution. In
combining data-driven short term predictions with long term distribution
assumptions our model is competitive to the existing methods in the short
horizon while yielding reasonable predictions in the long run. We apply our
model to interest rate data and contrast the forecasting performance to the one
of a 2-Additive-Factor Gaussian model as well as to the predictions of a
dynamic Nelson-Siegel model.

9
The categories of this paper are: nlin
8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
12
The categories of this paper are: nucl-th
13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
22
The categories of this paper are: chao-dyn
27
The categories of this paper are: comp-gas
29
The categories of this paper are: funct-an
4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg