The aim of this paper is to analyse the out-of-sample performance of SETAR models relative to a linear AR and a GARCH model using daily data for the Euro effective exchange rate. The evaluation is conducted on point, interval and density forecasts, unconditionally, over the whole forecast period, and conditional on specific regimes. The results show that overall the GARCH model is better able to capture the distributional features of the series and to predict higher-order moments than the SETAR models. However, from the results there is also a clear indication that the performance of the SETAR models improves significantly conditional on being on specific regimes
The forecast performance of the empirical ESTAR model of Taylor et al. (2001) is examined for 4 bila...
We compare a number of methods that have been proposed in the literature for obtaining h-step ahead ...
Abstract: A two-regime self-exciting threshold autoregressive process is estimated for quarterly agg...
The aim of this paper is to analyse the out-of-sample performance of SETAR models relative to a line...
The aim of this paper is to analyse the out-of-sample performance of SETAR models relative to a line...
The aim of this paper is to analyse the out-of-sample performance of SETAR models relative to a line...
The aim of this paper is to evaluate the forecasting performance of SETAR models with an application...
The aim of this paper is to compare the forecasting performance of SETAR and GARCH models against a ...
In this paper we investigate the multi-period forecast performance of a number of empirical selfexci...
We compare linear autoregressive (AR) models and self-exciting threshold autoregressive (SETAR) mode...
We consider the forecasting performance of two SETAR exchange rate models proposed by Krager and Kug...
The aim of this paper is to evaluate the forecasting performance of SETAR models with an application...
The forecast performance of the empirical ESTAR model of Taylor et al. (2001) is examined for 4 bila...
We compare a number of methods that have been proposed in the literature for obtaining h-step ahead ...
textabstractWe consider the usefulness of the two-regime SETAR model for out-of-sample forecasting, ...
The forecast performance of the empirical ESTAR model of Taylor et al. (2001) is examined for 4 bila...
We compare a number of methods that have been proposed in the literature for obtaining h-step ahead ...
Abstract: A two-regime self-exciting threshold autoregressive process is estimated for quarterly agg...
The aim of this paper is to analyse the out-of-sample performance of SETAR models relative to a line...
The aim of this paper is to analyse the out-of-sample performance of SETAR models relative to a line...
The aim of this paper is to analyse the out-of-sample performance of SETAR models relative to a line...
The aim of this paper is to evaluate the forecasting performance of SETAR models with an application...
The aim of this paper is to compare the forecasting performance of SETAR and GARCH models against a ...
In this paper we investigate the multi-period forecast performance of a number of empirical selfexci...
We compare linear autoregressive (AR) models and self-exciting threshold autoregressive (SETAR) mode...
We consider the forecasting performance of two SETAR exchange rate models proposed by Krager and Kug...
The aim of this paper is to evaluate the forecasting performance of SETAR models with an application...
The forecast performance of the empirical ESTAR model of Taylor et al. (2001) is examined for 4 bila...
We compare a number of methods that have been proposed in the literature for obtaining h-step ahead ...
textabstractWe consider the usefulness of the two-regime SETAR model for out-of-sample forecasting, ...
The forecast performance of the empirical ESTAR model of Taylor et al. (2001) is examined for 4 bila...
We compare a number of methods that have been proposed in the literature for obtaining h-step ahead ...
Abstract: A two-regime self-exciting threshold autoregressive process is estimated for quarterly agg...