Comparison of forecasting performance between MODWT-GARCH(1,1) and MODWT-EGARCH(1,1) models: Evidence from African stock markets
Many researchers documented that if stock markets' returns series are significantly skewed, linear-GARCH(1,1) grossly underestimates the forecast values of the returns. However, this study showed that the linear Maximal Overlap Discreet Wavelet Transform MODWT-GARCH(1,1) actually gives an acc...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2016
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| Subjects: | |
| Online Access: | http://eprints.usm.my/38472/1/Comparison_of_forecasting_performance_between_MODWT-GARCH%281%2C1%29_and_MODWT-EGARCH%281%2C1%29.pdf http://eprints.usm.my/38472/ http://www.keaipublishing.com/en/journals/jfds/ |
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| Summary: | Many researchers documented that if stock markets' returns series are significantly skewed, linear-GARCH(1,1) grossly underestimates
the forecast values of the returns. However, this study showed that the linear Maximal Overlap Discreet Wavelet
Transform MODWT-GARCH(1,1) actually gives an accurate forecast value of the returns. The study used the daily returns of four
African countries' stock market indices for the period January 2, 2000, to December 31, 2014. The Maximal Overlap Discreet
Wavelet Transform-GARCH(1,1) model and the Maximal Overlap Discreet Wavelet Transform-EGARCH(1,1) model are exhaustively
compared. The results show that although both models fit the returns data well, the forecast produced by the Maximal Overlap
Discreet Wavelet Transform-EGARCH(1,1) model actually underestimates the observed returns whereas the Maximal Overlap
Discreet Wavelet Transform-GARCH(1,1) model generates an accurate forecast value of the observed returns. |
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