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Modeling Daily Closing Price Volatility Using Symmetric Garch
| Content Provider | Semantic Scholar |
|---|---|
| Author | Fatima, Samreen Uddin, Mudassir |
| Copyright Year | 2019 |
| Abstract | Modeling and forecasting the volatility of daliy closing price series is a signifi cant area of fi nancial econometrics since last few decades. Due to regional integration of the fi nancial markets, investors not only interested in investing in their own countries stock markets but also investing in another countries stock markets. The aim of this study is to investigate the more volatile market and modelling the volatility.We use daily closing index of KSE-100 (Pakistan), BSESN (India) and CSE (Sri Lanka) as they are the member of SAARC countries covering the period 1st January, 2011 to 30th November, 2016. Empirical analysis shows that GARCH-inmean model is found insignifi cant for BSESN and CSE. It reveals that there is no relationship between risk and expected return. Furthermore, CSE is more persistent stock market than the other two, but KSE-100 is highly volatile during the study period. GARCH-in-mean model with log variance in mean return equation is suggested for out-sample forecast of KSE-100. On the other hand, in CSE IGARCH and for BSESN any one from IGARCH and GARCH are suggested suitable model. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://pbr.iobm.edu.pk/wp-content/uploads/2020/03/A-15.pdf |
| Alternate Webpage(s) | https://pbr.iobm.edu.pk/wp-content/uploads/2019/12/A-15.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
