The Performance of SETAR models by Regime: A Conditional Evaluation of Interval and Density Forecasts
AbstractThe aim of this paper is to analyse the out-of-sample performance of SETAR models using daily data for the Euro effective exchange rate. The evaluation is conducted on point, interval and density forecasts. The benchmark used for the comparison is a linear AR model for point forecast evaluation and a GARCH model for interval and density forecasts. In each case the models are evaluated unconditionally, over the whole forecast period, and conditionally, on the regimes of the SETAR models. The results show that, in general, the performance of the SETAR models improves significantly for the forecasts governed by the regime(s) with fewer observations. However, overall the GARCH model is better able to capture the distributional features of the series and to predict higher ordered moments.
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Bibliographic InfoPaper provided by Royal Economic Society in its series Royal Economic Society Annual Conference 2003 with number 147.
Date of creation: 04 Jun 2003
Date of revision:
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SETAR models; point forecasts; interval forecasts; density forecasts; Euro effective exchange rate;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
This paper has been announced in the following NEP Reports:
- NEP-ALL-2003-06-16 (All new papers)
- NEP-ECM-2003-06-19 (Econometrics)
- NEP-ETS-2003-06-16 (Econometric Time Series)
- NEP-IFN-2003-07-21 (International Finance)
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- repec:ntu:ntugeo:vol2-iss1-14-042 is not listed on IDEAS
- Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F, 2004. "Sensitivity of the Chi-Squared Goodness-of-Fit Test to the Partitioning of Data," The Warwick Economics Research Paper Series (TWERPS) 694, University of Warwick, Department of Economics.
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