Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data—Under Conditional Heteroskedasticity Framework
Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics. Blekinge Tekniska Högskola.ORCID iD: 0000-0002-7277-9151
Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
University of Mauritius, MUS.
2019 (English)In: Journal of Risk and Financial Management, Vol. 12, no 2Article in journal (Refereed) Published
Abstract [en]

This paper introduces Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data of unknown underlying distribution. The moments with conditional heteroscedasticity have been discussed. In a Monte Carlo experiment, it was found that the QML estimator performs as well as CLS and FGLS in terms of eliminating serial correlations, but the estimator can be sensitive to start value. Hence, two-stage QML has been suggested. In empirical estimation on two stock transaction data for Ericsson and AstraZeneca, the 2SQML turns out relatively more efficient than CLS and FGLS. The empirical results suggest that both of the series have long memory properties that imply that the impact of macroeconomic news or rumors in one point of time has a persistence impact on future transactions.

Place, publisher, year, edition, pages
Basel, 2019. Vol. 12, no 2
National Category
Probability Theory and Statistics Economics
Identifiers
URN: urn:nbn:se:bth-17901DOI: 10.3390/jrfm12020074OAI: oai:DiVA.org:bth-17901DiVA, id: diva2:1316267
Note

open access

Available from: 2019-05-16 Created: 2019-05-16 Last updated: 2019-05-21Bibliographically approved

Open Access in DiVA

fulltext(513 kB)17 downloads
File information
File name FULLTEXT01.pdfFile size 513 kBChecksum SHA-512
cfb2c4d3ba424536d1f0a8b5b0d0a7e275e9184a54430f41c50e0290b74fbfc323c7b823df88e5777575534257a519510956be907cde4eb5cec118a4b16564e4
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Authority records BETA

Quoreshi, Shahiduzzaman

Search in DiVA

By author/editor
Quoreshi, ShahiduzzamanUddin, Reaz
By organisation
Department of Industrial Economics
Probability Theory and StatisticsEconomics

Search outside of DiVA

GoogleGoogle Scholar
Total: 17 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 92 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf