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dc.contributor.authorHanafi A. Rahim-
dc.date.accessioned2013-03-18T03:20:10Z-
dc.date.available2013-03-18T03:20:10Z-
dc.date.issued2012-09-
dc.identifier.urihttp://dspace.psnz.umt.edu.my/xmlui/handle/123456789/2410-
dc.description.abstractThe general autoregressive conditional heteroscedasticity, (GARCH) family has become more efficient in fitting financial data as it consists of the second order moment that measures the time-variant of the volatility data. However, GARCH may fail to fit some high frequency financial data with large jumps called outliers. In this research, GARCH parameters were estimated using least absolute median (LAM).en_US
dc.language.isoenen_US
dc.publisher[Selangor]: Universiti Teknologi Maraen_US
dc.subjectQA 276.8 .H3 2012en_US
dc.subjectHanafi A. Rahimen_US
dc.subjectTesis Universiti Teknologi Mara 2012en_US
dc.subjectParameter estimationen_US
dc.titleGarch parameter estimation using least absolute medianen_US
dc.typeThesisen_US
Appears in Collections:Staff Thesis

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