Showing 1 - 10 of 48
In this paper we extend the parametric, asymmetric, stochastic volatility model (ASV), where returns are correlated with volatility, by flexibly modeling the bivariate distribution of the return and volatility innovations nonparametrically. Its novelty is in modeling the joint, conditional,...
Persistent link: https://www.econbiz.de/10010555040
This paper uses an infinite hidden Markov model (IHMM) to analyze U.S. inflation dynamics with a particular focus on the persistence of inflation. The IHMM is a Bayesian nonparametric approach to modeling structural breaks. It allows for an unknown number of breakpoints and is a flexible and...
Persistent link: https://www.econbiz.de/10008487525
This paper proposes a Bayesian nonparametric modeling approach for the return distribution in multivariate GARCH models. In contrast to the parametric literature the return distribution can display general forms of asymmetry and thick tails. An infinite mixture of multivariate normals is given a...
Persistent link: https://www.econbiz.de/10010556310
This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that by acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms.
Persistent link: https://www.econbiz.de/10010614521
In this paper we develop methods for estimation and forecasting in large time-varying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints with likelihood-based estimation of large systems, we rely on Kalman filter estimation with forgetting factors. We also...
Persistent link: https://www.econbiz.de/10010540685
We develop methods for Bayesian inference in vector error correction models which are subject to a variety of switches in regime (e.g. Markov switches in regime or structural breaks). An important aspect of our approach is that we allow both the cointegrating vectors and the number of...
Persistent link: https://www.econbiz.de/10009320949
The Hodrick-Prescott (HP) method is a popular smoothing method for economic time series to get a smooth or long-term component of stationary series like growth rates. We show that the HP smoother can be viewed as a Bayesian linear model with a strong prior using differencing matrices for the...
Persistent link: https://www.econbiz.de/10009364166
The Hodrick-Prescott (HP) method is a popular smoothing method for economic time series to get a longterm component of stationary series like growth rates. The new extended HP smoothing model is applied to data-sets with an underlying metric and requires a Bayesian linear regression model with a...
Persistent link: https://www.econbiz.de/10009364167
This paper proposes an infinite hidden Markov model (iHMM) to detect, date stamp, and estimate speculative bubbles. Three features make this new approach attractive to practitioners. first, the iHMM is capable of capturing the nonlinear dynamics of different types of bubble behaviors as it...
Persistent link: https://www.econbiz.de/10010551744
This paper proposes an infinite hidden Markov model to integrate the regime switching and the structural break dynamics in a single, coherent Bayesian framework. Two parallel hierarchical structures, one governing the transition probabilities and another governing the parameters of the...
Persistent link: https://www.econbiz.de/10010551751