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forecasting, however it is robust in the sense that it provides a more accurate estimation of the predictive density in the region …
Persistent link: https://www.econbiz.de/10012057160
Vector autoregressions have steadily gained in popularity since their introduction in econometrics 25 years ago. A drawback of the otherwise fairly well developed methodology is the inability to incorporate prior beliefs regarding the system's steady state in a satisfactory way. Such prior...
Persistent link: https://www.econbiz.de/10011585058
During the year 2016, the Central Bank of Argentina has begun to announce inflation targets. In this context, providing the authorities of good estimates of relevant macroeconomic variables turns out to be crucial to make the pertinent corrections to reach the desired policy goals. This paper...
Persistent link: https://www.econbiz.de/10011846246
In 2016 the Central Bank of Argentina began to announce inflation targets. In this context, providing authorities with good estimates of relevant macroeconomic variables is crucial for making pertinent corrections in order to reach the desired policy goals. This paper develops a group of models...
Persistent link: https://www.econbiz.de/10011882797
forecasting volatility model with the most appropriate error distribution. The results suggest the presence of leverage effect … validate this result. The last twenty eight days out-of-sample forecast adjudged Power-GARCH (1, 1, 1) in student's t error … forecasting model that could guarantee a sound policy decisions. …
Persistent link: https://www.econbiz.de/10011489480
Using well-known GARCH models for density prediction of daily S&P 500 and Nikkei 225 index returns, a comparison is …
Persistent link: https://www.econbiz.de/10012976219
We develop efficient simulation techniques for Bayesian inference on switching GARCH models. Our contribution to … space models with particular attention to MS-GARCH models. Our multi-move sampling strategy is based on the Forward … Filtering Backward Sampling (FFBS) applied to an approximation of MS-GARCH. Another important contribution is the use of multi …
Persistent link: https://www.econbiz.de/10013088788
This paper proposes a Bayesian nonparametric modeling approach for the return distribution in multivariate GARCH models …. An infinite mixture of multivariate normals is given a flexible Dirichlet process prior. The GARCH functional form enters … posterior simulation and computation of the predictive density. Bayes factors and density forecasts with comparisons to GARCH …
Persistent link: https://www.econbiz.de/10009565827
Efficient posterior simulators for two GARCH models with generalized hyperbolic disturbances are presented. The first … model, GHt-GARCH, is a threshold GARCH with a skewed and heavy-tailed error distribution; in this model, the latent … variables that account for skewness and heavy tails are identically and independently distributed. The second model, ODLV-GARCH …
Persistent link: https://www.econbiz.de/10013105412
This paper proposes a Bayesian nonparametric modeling approach for the return distribution in multivariate GARCH models …. An infinite mixture of multivariate normals is given a flexible Dirichlet process prior. The GARCH functional form enters … posterior simulation and computation of the predictive density. Bayes factors and density forecasts with comparisons to GARCH …
Persistent link: https://www.econbiz.de/10013065708