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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Bibliographic Details
Main Author: A.Rahim, Hanafi
Format: Book Section
Language:English
Published: Institute of Graduate Studies, UiTM 2012
Subjects:
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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Summary: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).