Volatility forecasting with the wavelet transformation algorithm GARCH model: Evidence from African stock markets
The daily returns of four African countries' stock market indices for the period January 2, 2000, to December 31, 2014, were employed to compare the GARCH(1,1) model and a newly proposed Maximal Overlap Discreet Wavelet Transform (MODWT)- GARCH(1,1) model. The results showed that although bot...
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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/37283/1/%28Volatility_forecasting_with_the_wavelet%29_1-s2.0-S240591881630006X-main.pdf http://eprints.usm.my/37283/ https://doi.org/10.1016/j.jfds.2016.09.002 |
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| Summary: | The daily returns of four African countries' stock market indices for the period January 2, 2000, to December 31, 2014, were
employed to compare the GARCH(1,1) model and a newly proposed Maximal Overlap Discreet Wavelet Transform (MODWT)-
GARCH(1,1) model. The results showed that although both models fit the returns data well, the forecast produced by the GARCH(1,1)
model underestimates the observed returns whereas the newly proposed MODWT-GARCH(1,1) model generates an accurate
forecast value of the observed returns. The results generally showed that the newly proposed MODWT-GARCH(1,1) model best fits
returns series for these African countries. Hence the proposed MODWT-GARCH should be applied on other context to further
verify its validity. |
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