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GARCH Parameter estimation using least absolute median / Hanafi A.Rahim

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: A.Rahim, Hanafi
Format: Book Section
Language:English
Published: Institute of Graduate Studies, UiTM 2012
Subjects:
Malaysia
Online Access:http://ir.uitm.edu.my/id/eprint/19184/1/ABS_HANAFI%20A.RAHIM%20TDRA%20VOL%202%20IGS%2012.pdf
http://ir.uitm.edu.my/id/eprint/19184/
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spelling my.uitm.ir.191842018-06-12T01:27:41Z http://ir.uitm.edu.my/id/eprint/19184/ GARCH Parameter estimation using least absolute median / Hanafi A.Rahim A.Rahim, Hanafi Malaysia 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). Institute of Graduate Studies, UiTM 2012 Book Section PeerReviewed text en http://ir.uitm.edu.my/id/eprint/19184/1/ABS_HANAFI%20A.RAHIM%20TDRA%20VOL%202%20IGS%2012.pdf A.Rahim, Hanafi (2012) GARCH Parameter estimation using least absolute median / Hanafi A.Rahim. In: The Doctoral Research Abstracts. IPSis Biannual Publication, 2 . Institute of Graduate Studies, UiTM, Shah Alam.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Malaysia
spellingShingle Malaysia
A.Rahim, Hanafi
GARCH Parameter estimation using least absolute median / Hanafi A.Rahim
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 Book Section
author A.Rahim, Hanafi
author_facet A.Rahim, Hanafi
author_sort A.Rahim, Hanafi
title GARCH Parameter estimation using least absolute median / Hanafi A.Rahim
title_short GARCH Parameter estimation using least absolute median / Hanafi A.Rahim
title_full GARCH Parameter estimation using least absolute median / Hanafi A.Rahim
title_fullStr GARCH Parameter estimation using least absolute median / Hanafi A.Rahim
title_full_unstemmed GARCH Parameter estimation using least absolute median / Hanafi A.Rahim
title_sort garch parameter estimation using least absolute median / hanafi a.rahim
publisher Institute of Graduate Studies, UiTM
publishDate 2012
url http://ir.uitm.edu.my/id/eprint/19184/1/ABS_HANAFI%20A.RAHIM%20TDRA%20VOL%202%20IGS%2012.pdf
http://ir.uitm.edu.my/id/eprint/19184/
_version_ 1685649178869366784
score 13.160551

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