Cover Image

Mistakes in the real-time identification of breaks

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

Full description

Saved in:
Bibliographic Details
Main Authors: Mazlan, Nur Syazwani, Bulkley, George
Format: Conference or Workshop Item
Language:English
Published: Faculty of Economics and Management, Universiti Putra Malaysia 2017
Online Access:http://psasir.upm.edu.my/id/eprint/58705/1/8-nur_syazwani.pdf.pdf
http://psasir.upm.edu.my/id/eprint/58705/
http://www.econ.upm.edu.my/upload/dokumen/20170816181502024-nur_syazwani.pdf.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.upm.eprints.58705
record_format eprints
spelling my.upm.eprints.587052018-01-29T10:11:42Z http://psasir.upm.edu.my/id/eprint/58705/ Mistakes in the real-time identification of breaks Mazlan, Nur Syazwani Bulkley, George We study the mistakes that happen in the real-time identification of structural breaks in the selected aggregate-level of the U.S. financial data series. We are interested in the real time identification because of its relevance for forecasting. The level of noisiness of different data sets and techniques used for the identification of breaks affect the frequency of mistakes encountered in real time. We find that mistakes in not finding the true breaks and/or finding the wrong ones in real time are made more frequently in the case of a noisier financial data set. Moreover, the techniques for optimal break detection based on sequential learning of the Bai and Perron (2003) are found to make fewer mistakes than those based on Information Criteria (IC). Faculty of Economics and Management, Universiti Putra Malaysia 2017 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/58705/1/8-nur_syazwani.pdf.pdf Mazlan, Nur Syazwani and Bulkley, George (2017) Mistakes in the real-time identification of breaks. In: Global Conference on Business and Economics Research (GCBER) 2017, 14-15 Aug. 2017, Universiti Putra Malaysia, Serdang, Selangor. (pp. 189-196). http://www.econ.upm.edu.my/upload/dokumen/20170816181502024-nur_syazwani.pdf.pdf
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description We study the mistakes that happen in the real-time identification of structural breaks in the selected aggregate-level of the U.S. financial data series. We are interested in the real time identification because of its relevance for forecasting. The level of noisiness of different data sets and techniques used for the identification of breaks affect the frequency of mistakes encountered in real time. We find that mistakes in not finding the true breaks and/or finding the wrong ones in real time are made more frequently in the case of a noisier financial data set. Moreover, the techniques for optimal break detection based on sequential learning of the Bai and Perron (2003) are found to make fewer mistakes than those based on Information Criteria (IC).
format Conference or Workshop Item
author Mazlan, Nur Syazwani
Bulkley, George
spellingShingle Mazlan, Nur Syazwani
Bulkley, George
Mistakes in the real-time identification of breaks
author_facet Mazlan, Nur Syazwani
Bulkley, George
author_sort Mazlan, Nur Syazwani
title Mistakes in the real-time identification of breaks
title_short Mistakes in the real-time identification of breaks
title_full Mistakes in the real-time identification of breaks
title_fullStr Mistakes in the real-time identification of breaks
title_full_unstemmed Mistakes in the real-time identification of breaks
title_sort mistakes in the real-time identification of breaks
publisher Faculty of Economics and Management, Universiti Putra Malaysia
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/58705/1/8-nur_syazwani.pdf.pdf
http://psasir.upm.edu.my/id/eprint/58705/
http://www.econ.upm.edu.my/upload/dokumen/20170816181502024-nur_syazwani.pdf.pdf
_version_ 1643836862693900288
score 13.211869

Similar Items