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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| Format: | Book Section |
| Language: | English |
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Institute of Graduate Studies, UiTM
2012
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| Online Access: | http://ir.uitm.edu.my/id/eprint/19184/ http://ir.uitm.edu.my/id/eprint/19184/1/ABS_HANAFI%20A.RAHIM%20TDRA%20VOL%202%20IGS%2012.pdf |
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eprints |
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uitm-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. |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
Universiti Teknologi MARA |
| building |
UiTM Institutional Repository |
| collection |
Online Access |
| 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/ http://ir.uitm.edu.my/id/eprint/19184/1/ABS_HANAFI%20A.RAHIM%20TDRA%20VOL%202%20IGS%2012.pdf |
| first_indexed |
2023-09-18T23:02:01Z |
| last_indexed |
2023-09-18T23:02:01Z |
| _version_ |
1777418236599468032 |