Autoregressive Lag Length Selection Criteria in the Presence of ARCH Errors
We study the effects of ARCH errors on the performance of the commonly used lag length selection criteria. The most important finding of this study is that SIC, FPE, HQC and BIC perform considerably well in estimating the true autoregressive lag length, even in the presence of ARCH errors. Thus, we...
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Orebro University School of Business
2005
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Online Access: | http://ir.unimas.my/id/eprint/18631/7/Autoregressive%20Lag%20Length%20Selection%20Criteria%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/18631/ https://econpapers.repec.org/article/eblecbull/eb-05c20011.htm |
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my.unimas.ir.186312017-11-21T01:46:45Z http://ir.unimas.my/id/eprint/18631/ Autoregressive Lag Length Selection Criteria in the Presence of ARCH Errors Liew, Venus Khim-Sen Chong, Terence Tai-Leung HB Economic Theory We study the effects of ARCH errors on the performance of the commonly used lag length selection criteria. The most important finding of this study is that SIC, FPE, HQC and BIC perform considerably well in estimating the true autoregressive lag length, even in the presence of ARCH errors. Thus, we conclude that these criteria are applicable to empirical data such as stock market returns and exchange rate volatility that exhibit ARCH effects. Orebro University School of Business 2005-04-01 E-Article PeerReviewed text en http://ir.unimas.my/id/eprint/18631/7/Autoregressive%20Lag%20Length%20Selection%20Criteria%20%28abstract%29.pdf Liew, Venus Khim-Sen and Chong, Terence Tai-Leung (2005) Autoregressive Lag Length Selection Criteria in the Presence of ARCH Errors. Economics Bulletin, 3 (19). pp. 1-5. ISSN 1545-2921 https://econpapers.repec.org/article/eblecbull/eb-05c20011.htm |
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HB Economic Theory Liew, Venus Khim-Sen Chong, Terence Tai-Leung Autoregressive Lag Length Selection Criteria in the Presence of ARCH Errors |
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We study the effects of ARCH errors on the performance of the commonly used lag length selection criteria. The most important finding of this study is that SIC, FPE, HQC and BIC perform considerably well in estimating the true autoregressive lag length, even in the presence of ARCH errors. Thus, we conclude that these criteria are applicable to empirical data such as stock market returns and exchange rate volatility that exhibit ARCH effects. |
format |
E-Article |
author |
Liew, Venus Khim-Sen Chong, Terence Tai-Leung |
author_facet |
Liew, Venus Khim-Sen Chong, Terence Tai-Leung |
author_sort |
Liew, Venus Khim-Sen |
title |
Autoregressive Lag Length Selection Criteria in the Presence of ARCH Errors |
title_short |
Autoregressive Lag Length Selection Criteria in the Presence of ARCH Errors |
title_full |
Autoregressive Lag Length Selection Criteria in the Presence of ARCH Errors |
title_fullStr |
Autoregressive Lag Length Selection Criteria in the Presence of ARCH Errors |
title_full_unstemmed |
Autoregressive Lag Length Selection Criteria in the Presence of ARCH Errors |
title_sort |
autoregressive lag length selection criteria in the presence of arch errors |
publisher |
Orebro University School of Business |
publishDate |
2005 |
url |
http://ir.unimas.my/id/eprint/18631/7/Autoregressive%20Lag%20Length%20Selection%20Criteria%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/18631/ https://econpapers.repec.org/article/eblecbull/eb-05c20011.htm |
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