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...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
[Selangor]: Universiti Teknologi Mara
2013
|
| Subjects: | |
| Online Access: | http://dspace.psnz.umt.edu.my/xmlui/handle/123456789/2410 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| 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). |
|---|