Identifying multiple structural breaks in exchange rate series in a finance research

A. Zarei, M. Ariff, L.S. Hook, A.M. Nassir

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
1048 Downloads (Pure)


This paper describes how to resolve a recurrent research problem in finance research, that is,how to identify and then take steps to correct structural breakpoints in time series data sets.A review of finance literature suggests that the familiar method of identifying breaks is by using news reports of events, which is not accurate in a formal sense, and will likely introduce estimation errors in research. There exist formal models, which are used to accurately identify breaks especially in long-time series to pre-test exchange rate data series as a pre-analysis stepto accurately locate breaks that will help control estimation errors introduced from breakpoint impacts. The findings from testing four-country data series, using 651 months data of each country, suggested that the method described in this study identified breakpoints accurately,which was also verified using graphs. Therefore, it is suggested that this process is helpful for researchers to formally identify structural breakpoints as it greatly improves the robustness of estimation of exchange rate behaviour (apart from other financial variables).
Original languageEnglish
Pages (from-to)155 – 166
Number of pages12
JournalPertanika Journal of Social Sciences and Humanities
Issue numberSeptember Special Issue
Publication statusPublished - Sept 2015
Externally publishedYes

Bibliographical note

Open-access online scientific journal.


  • Multiple Structural breaks
  • Time series analysis
  • Exchange rates
  • Bai-Perron Model


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