Garch parameter estimation using least absolute median

Please use this identifier to cite or link to this item: http://umt-ir.umt.edu.my:8080/handle/123456789/2410

Full metadata record

DC Field	Value	Language
dc.contributor.author	Hanafi A. Rahim	-
dc.date.accessioned	2013-03-18T03:20:10Z	-
dc.date.available	2013-03-18T03:20:10Z	-
dc.date.issued	2012-09	-
dc.identifier.uri	http://dspace.psnz.umt.edu.my/xmlui/handle/123456789/2410	-
dc.description.abstract	The 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.iso	en	en_US
dc.publisher	[Selangor]: Universiti Teknologi Mara	en_US
dc.subject	QA 276.8 .H3 2012	en_US
dc.subject	Hanafi A. Rahim	en_US
dc.subject	Tesis Universiti Teknologi Mara 2012	en_US
dc.subject	Parameter estimation	en_US
dc.title	Garch parameter estimation using least absolute median	en_US
dc.type	Thesis	en_US
Appears in Collections:	Staff Thesis

Files in This Item:

File	Description	Size	Format
QA 276.8 .H3 2012 Abstract.pdf		326.63 kB	Adobe PDF	View/Open
QA 276.8 .H3 2012 FullText.pdf Restricted Access		3.22 MB	Adobe PDF	View/Open Request a copy

DSpace JSPUI