Construction of multi-step forecast regions of VAR processes using ordered block bootstrap
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, cilt.50, ss.2107-2125, 2021 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 50
- Basım Tarihi: 2021
- Doi Numarası: 10.1080/03610918.2019.1596282
- Dergi Adı: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Business Source Elite, Business Source Premier, CAB Abstracts, Compendex, Computer & Applied Sciences, Veterinary Science Database, zbMATH, Civil Engineering Abstracts
- Sayfa Sayıları: ss.2107-2125
- Anahtar Kelimeler: Block bootstrap, Vector autoregressive model, Multivariate forecast, Forecast region
- Dokuz Eylül Üniversitesi Adresli: Hayır
Özet
In this study, an ordered non-overlapping block bootstrap procedure has been proposed to obtain multi-step forecast regions for unrestricted vector autoregressive models. The proposed method is not based on either backward or forward representations, so it can be implemented to VARMA or VAR-GARCH models. Also, it is computationally more efficient than the existing techniques. Its finite sample performance is investigated by Monte Carlo experiments and two-real world examples. Our findings show that the proposed method is a good alternative to the available resampling methods and produces better results for long-term forecasting when the model is near non-stationary or near-cointegrated.