Error in the real-time identification of breaks

We studied the mistakes that happen in the real-time identification of structural breaks in the selected aggregate-level of U.S. financial data series. We were interested in the real-time identification because of its relevance for forecasting. The level of the noisiness of different datasets and te...

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Main Authors: Mazlan, Nur Syazwani, Bulkley, George
Format: Article
Language:English
Published: Faculty of Economics and Management, Universiti Putra Malaysia 2018
Online Access:http://psasir.upm.edu.my/id/eprint/16091/
http://psasir.upm.edu.my/id/eprint/16091/1/13%29%20Error%20in%20the%20Real%20Time.pdf
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author Mazlan, Nur Syazwani
Bulkley, George
author_facet Mazlan, Nur Syazwani
Bulkley, George
author_sort Mazlan, Nur Syazwani
building UPM Institutional Repository
collection Online Access
description We studied the mistakes that happen in the real-time identification of structural breaks in the selected aggregate-level of U.S. financial data series. We were interested in the real-time identification because of its relevance for forecasting. The level of the noisiness of different datasets and techniques used for the identification of breaks affected the frequency of the mistakes encountered in real-time. We found that mistakes in not finding the true breaks and/or finding the wrong ones in real-time were made more frequently in the case of a noisier financial dataset. Moreover, the techniques for optimal break detection based on the sequential learning of Bai and Perron (2003) were found to make fewer mistakes than those based on the Information Criteria (IC).
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spelling upm-160912019-11-12T06:58:48Z http://psasir.upm.edu.my/id/eprint/16091/ Error in the real-time identification of breaks Mazlan, Nur Syazwani Bulkley, George We studied the mistakes that happen in the real-time identification of structural breaks in the selected aggregate-level of U.S. financial data series. We were interested in the real-time identification because of its relevance for forecasting. The level of the noisiness of different datasets and techniques used for the identification of breaks affected the frequency of the mistakes encountered in real-time. We found that mistakes in not finding the true breaks and/or finding the wrong ones in real-time were made more frequently in the case of a noisier financial dataset. Moreover, the techniques for optimal break detection based on the sequential learning of Bai and Perron (2003) were found to make fewer mistakes than those based on the Information Criteria (IC). Faculty of Economics and Management, Universiti Putra Malaysia 2018 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/16091/1/13%29%20Error%20in%20the%20Real%20Time.pdf Mazlan, Nur Syazwani and Bulkley, George (2018) Error in the real-time identification of breaks. International Journal of Economics and Management, 12 (spec. 2). pp. 469-477. ISSN 1823-836X; ESSN: 2600-9390 http://www.ijem.upm.edu.my/vol12_noS2/13)%20Error%20in%20the%20Real%20Time.pdf
spellingShingle Mazlan, Nur Syazwani
Bulkley, George
Error in the real-time identification of breaks
title Error in the real-time identification of breaks
title_full Error in the real-time identification of breaks
title_fullStr Error in the real-time identification of breaks
title_full_unstemmed Error in the real-time identification of breaks
title_short Error in the real-time identification of breaks
title_sort error in the real-time identification of breaks
url http://psasir.upm.edu.my/id/eprint/16091/
http://psasir.upm.edu.my/id/eprint/16091/
http://psasir.upm.edu.my/id/eprint/16091/1/13%29%20Error%20in%20the%20Real%20Time.pdf