THE PERFORMANCE OF SETAR MODELS: A REGIME CONDITIONAL EVALUATION OF POINT, INTERVAL AND DENSITY FORECASTS
By Gianna Boero, Emanuela Marrocu. 2004
70 citations recorded by the source corpus.
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.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/5052a2f1204d3094111023c4740cd8c2281b1655
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In Economics and Econometrics
- J. De Gooijer
- Isabel Pereira
- Magda Monteiro
- Rob J Hyndman
- Manuel G. Scotto
- Alexei Botchkarev
- Konstantinos Nikolopoulos
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In Finance
- Isabel Pereira
- Magda Monteiro
- Rob J Hyndman
- J. De Gooijer
- Manuel G. Scotto
- Konstantinos Fokianos
- P. Pollett
- Christian H. Weiβ
Citations in the corpus
- 25 years of time series forecasting (2006, methodology): “The out-of-sample forecast performance of various variants of SETAR models relative to linear models has been the subject of several IJF papers, including Astatkie et al. (1997), Boero & Marrocu (2004) and Enders & Falk (1998).”
- 25 Years of IIF Time Series Forecasting: A Selective Review (2005, methodology): “The out-of-sample forecast performance of various variants of SETAR models relative to linear models has been the subject of several IJF papers, including Astatkie et al. (1997), Boero & Marrocu (2004) and Enders & Falk (1998).”
- Integer-Valued Self-Exciting Threshold Autoregressive Processes (2012, background): “Since their introduction by Tong (1977), much attention has been given to threshold models partially because of their wide applicability to economy and finance (Boero and Marrocu, 2004; Pai and Pedersen, 1999; Potter, 1995), hydrological (Fu et al.”