Artikel
A Bayesian time‐varying autoregressive model for improved short‐term and long‐term prediction
Motivated by the application to German interest rates, we propose a time‐varying autoregressive model for short‐term and long‐term prediction of time series that exhibit a temporary nonstationary 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 that of a 2‐Additive‐Factor Gaussian model as well as to the predictions of a dynamic Nelson‐Siegel model.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Journal of Forecasting ; ISSN: 1099-131X ; Volume: 41 ; Year: 2021 ; Issue: 1 ; Pages: 181-200
- Thema
-
Bayesian time‐varying autoregressive models
Gibbs sampler
interest rate models
long run regularization
MCMC metropolis‐Hastings
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Berninger, Christoph
Stöcker, Almond
Rügamer, David
- Ereignis
-
Veröffentlichung
- (wer)
-
Wiley
- (wo)
-
Hoboken, NJ
- (wann)
-
2021
- DOI
-
doi:10.1002/for.2802
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Berninger, Christoph
- Stöcker, Almond
- Rügamer, David
- Wiley
Entstanden
- 2021
Ähnliche Objekte (12)
A Bayesian time-varying autoregressive model for improved short‐term and long‐term prediction
Robust shift detection in time-varying autoregressive processes
Robust shift detection in time-varying autoregressive processes
Nonlinear Wavelet Estimation of Time-Varying Autoregressive Processes
Nonlinear Wavelet Estimation of Time-Varying Autoregressive Processes
Time-varying first-order autoregressive processes with irregular innovations
Bayesian time‐varying autoregressive models of COVID‐19 epidemics
Modeling the US short-term interest rate by mixture autoregressive processes
Modeling the U.S. Short-Term Interest Rate by Mixture Autoregressive Processes
Choosing Between Different Time-Varying Volatility Models for Structural Vector Autoregressive Analysis
Choosing between different time-varying volatility models for structural vector autoregressive analysis
Choosing between different time-varying volatility models for structural vector autoregressive analysis
A Bayesian time-varying autoregressive model for improved short‐term and long‐term prediction
Robust shift detection in time-varying autoregressive processes
Robust shift detection in time-varying autoregressive processes
Nonlinear Wavelet Estimation of Time-Varying Autoregressive Processes
Nonlinear Wavelet Estimation of Time-Varying Autoregressive Processes
Time-varying first-order autoregressive processes with irregular innovations
Bayesian time‐varying autoregressive models of COVID‐19 epidemics
Modeling the US short-term interest rate by mixture autoregressive processes
Modeling the U.S. Short-Term Interest Rate by Mixture Autoregressive Processes
Choosing Between Different Time-Varying Volatility Models for Structural Vector Autoregressive Analysis
Choosing between different time-varying volatility models for structural vector autoregressive analysis
Choosing between different time-varying volatility models for structural vector autoregressive analysis
A Bayesian time-varying autoregressive model for improved short‐term and long‐term prediction
Robust shift detection in time-varying autoregressive processes
Robust shift detection in time-varying autoregressive processes
Nonlinear Wavelet Estimation of Time-Varying Autoregressive Processes
Nonlinear Wavelet Estimation of Time-Varying Autoregressive Processes
Time-varying first-order autoregressive processes with irregular innovations
Bayesian time‐varying autoregressive models of COVID‐19 epidemics
Modeling the US short-term interest rate by mixture autoregressive processes
Modeling the U.S. Short-Term Interest Rate by Mixture Autoregressive Processes
Choosing Between Different Time-Varying Volatility Models for Structural Vector Autoregressive Analysis
Choosing between different time-varying volatility models for structural vector autoregressive analysis