A study of structural breaks in Malaysian stock market

Authors

  • Mohd Tahir Ismail1
  • Samsul Ariffin Abdul Karim2
  • S. Alwadi1

Keywords:

Structural breaks, financial time series, Markov switching model, wavelets transform

Abstract

In recent years the study of regime shifts or structural breaks behaviour in time series has gained much
attention. This is due to realization that many economic time series undergo episodes in which the
behaviour of the series change quite dramatically as a result of financial crises or abrupt changes in the
government policy. The paper use two difference approaches to capture the possibility of structural
breaks in KLCI index of Bursa Malaysia between 1977 and 2008. The first approach is by using the
Markov switching model where the movement between regimes or regime shifts are unrelated to the
past observations of the process and enables probabilistic statements to be made about the likelihood
of the series being in a particular regime in any time period. While the second approach is via the
wavelets method where a time series is transform using a particular wavelet basis functions. The
transform series is well localized in both the time (position) and the frequency (scale) domain. Hence,
the study can detect precisely a sudden change in the data. Finally, the study compares the results
from the two approaches and discusses the advantage and disadvantage of each approach. Several
numerical results will be presented.

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Published

2021-11-15