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Garch parameter estimation using least absolute median

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...

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Main Author: Hanafi A. Rahim
Format: Thesis
Language:English
Published: [Selangor]: Universiti Teknologi Mara 2013
Subjects:
QA 276.8 .H3 2012
Hanafi A. Rahim
Tesis Universiti Teknologi Mara 2012
Parameter estimation
Online Access:http://dspace.psnz.umt.edu.my/xmlui/handle/123456789/2410
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id my.umt.ir-2410
record_format eprints
spelling my.umt.ir-24102013-03-18T03:20:10Z Garch parameter estimation using least absolute median Hanafi A. Rahim QA 276.8 .H3 2012 Hanafi A. Rahim Tesis Universiti Teknologi Mara 2012 Parameter estimation 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). 2013-03-18T03:20:10Z 2013-03-18T03:20:10Z 2012-09 Thesis http://dspace.psnz.umt.edu.my/xmlui/handle/123456789/2410 en application/pdf application/pdf [Selangor]: Universiti Teknologi Mara
institution Universiti Malaysia Terengganu
building Perpustakaan Sultanah Nur Zahirah
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Terengganu
content_source UMT-IR
url_provider http://umt-ir.umt.edu.my:8080/
language English
topic QA 276.8 .H3 2012
Hanafi A. Rahim
Tesis Universiti Teknologi Mara 2012
Parameter estimation
spellingShingle QA 276.8 .H3 2012
Hanafi A. Rahim
Tesis Universiti Teknologi Mara 2012
Parameter estimation
Hanafi A. Rahim
Garch parameter estimation using least absolute median
description 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).
format Thesis
author Hanafi A. Rahim
author_facet Hanafi A. Rahim
author_sort Hanafi A. Rahim
title Garch parameter estimation using least absolute median
title_short Garch parameter estimation using least absolute median
title_full Garch parameter estimation using least absolute median
title_fullStr Garch parameter estimation using least absolute median
title_full_unstemmed Garch parameter estimation using least absolute median
title_sort garch parameter estimation using least absolute median
publisher [Selangor]: Universiti Teknologi Mara
publishDate 2013
url http://dspace.psnz.umt.edu.my/xmlui/handle/123456789/2410
_version_ 1738395430146801664
score 13.214268

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