DocumentCode
2220925
Title
The Relative Performance of VAR and VECM Model
Author
Zhang, Jianfeng ; Hu, Wenxiu ; Zhang, Xin
Author_Institution
Dept. of Finance, Xi´´an Univ. of Technol., Xi´´an, China
Volume
2
fYear
2010
fDate
26-28 Nov. 2010
Firstpage
132
Lastpage
135
Abstract
Two models are examined in this study: Vector Autoregressive Model (VAR) and Vector Error Correction Model (VECM). Based on three indices: S&P 500, Nikkei 225 (NIKKEI), and Morgan Stanley EAFE (MSCIEAFE or MSCI EAFE) Index, we implement VAR and VECM models, including the pre-estimation diagnostics, model estimation and interpretation and post-estimation tests, etc. By testing, we find that while the VECM model consistently outperforms the VAR model within sample, it is hard to tell which works better out-of-sample. Our examination suggests four conclusions: First, both models do the best job with MSCI EAFE. Second, VECM model does a better job within sample. Third, both models create less error out-of-sample than within sample. Fourth, VECM model does a better job than VAR in S&P 500 and NIKKEI.
Keywords
autoregressive processes; error correction; forecasting theory; Morgan Stanley EAFE Index; Nikkei 225; S&P 500; VAR model; VECM model; model estimation; post estimation test; preestimation diagnostics; relative performance; vector autoregressive model; vector error correction model; Cointegration Estimation; Forecasting Performance; VAR Model; VECM Model;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Management, Innovation Management and Industrial Engineering (ICIII), 2010 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-8829-2
Type
conf
DOI
10.1109/ICIII.2010.195
Filename
5694534
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