Long memory analysis by using maximal overlapping discrete wavelet transform

Nur Amalina Binti Shafie, Mohd Tahir Ismail, Zaidi Isa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Long memory process is the asymptotic decay of the autocorrelation or spectral density around zero. The main objective of this paper is to do a long memory analysis by using the Maximal Overlapping Discrete Wavelet Transform (MODWT) based on wavelet variance. In doing so, stock market of Malaysia, China, Singapore, Japan and United States of America are used. The risk of long term and short term investment are also being looked into. MODWT can be analyzed with time domain and frequency domain simultaneously and decomposing wavelet variance to different scales without loss any information. All countries under studied show that they have long memory. Subprime mortgage crisis in 2007 is occurred in the United States of America are possible affect to the major trading countries. Short term investment is more risky than long term investment.

Original languageEnglish
Title of host publicationInternational Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014
PublisherAmerican Institute of Physics Inc.
Volume1660
ISBN (Electronic)9780735413047
DOIs
Publication statusPublished - 15 May 2015
EventInternational Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014 - Penang, Malaysia
Duration: 28 May 201430 May 2014

Other

OtherInternational Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014
CountryMalaysia
CityPenang
Period28/5/1430/5/14

Fingerprint

wavelet analysis
Malaysia
Singapore
autocorrelation
China
Japan
decay

Keywords

  • Long memory
  • MODWT
  • stock market

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Shafie, N. A. B., Ismail, M. T., & Isa, Z. (2015). Long memory analysis by using maximal overlapping discrete wavelet transform. In International Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014 (Vol. 1660). [090027] American Institute of Physics Inc.. https://doi.org/10.1063/1.4915871

Long memory analysis by using maximal overlapping discrete wavelet transform. / Shafie, Nur Amalina Binti; Ismail, Mohd Tahir; Isa, Zaidi.

International Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014. Vol. 1660 American Institute of Physics Inc., 2015. 090027.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shafie, NAB, Ismail, MT & Isa, Z 2015, Long memory analysis by using maximal overlapping discrete wavelet transform. in International Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014. vol. 1660, 090027, American Institute of Physics Inc., International Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014, Penang, Malaysia, 28/5/14. https://doi.org/10.1063/1.4915871
Shafie NAB, Ismail MT, Isa Z. Long memory analysis by using maximal overlapping discrete wavelet transform. In International Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014. Vol. 1660. American Institute of Physics Inc. 2015. 090027 https://doi.org/10.1063/1.4915871
Shafie, Nur Amalina Binti ; Ismail, Mohd Tahir ; Isa, Zaidi. / Long memory analysis by using maximal overlapping discrete wavelet transform. International Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014. Vol. 1660 American Institute of Physics Inc., 2015.
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