Generalised Autoregressive Conditional Heteroscedasticity (Garch) Models For Stock Market Volatility
The performance of generalised autoregressive conditional heteroscedasticity (GARCH) model and its modifications in forecasting stock market volatility are evaluated using the rate of returns from the daily stock market indices of Kuala Lumpur Stock Exchange (KLSE). These indices include Composi...
Saved in:
| Main Author: | Choo, Wei Chong |
|---|---|
| Format: | Thesis |
| Language: | English English |
| Published: |
1998
|
| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/11298/1/FSAS_1998_1_A.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Generalised autoregressive conditional heteroscedasticity (GARCH) models for stock market volatility /
by: Choo, Wei Chong. -
Generalised Autoregressive Conditional Heteroscedasticity (Garch) Models For Stock Market Volatility
by: Choo, Wei Chong
Published: (1998) -
Market Efficiency in the Kuala Lumpur Stock Exchange:
Further Evidence Using Garch Model
by: Aru Bol, Victoria Samuel
Published: (2001) -
The Malaysian stock market /
by: S. Loganathan. -
Market efficiency in the Kuala Lumpur Stock Exchange : further evidence using garch model /
by: Aru Bol, Victoria Samuel.
