Volatility forecasting with the wavelet transformation algorithm GARCH model: Evidence from African stock markets

• Main Authors: Ismail, Mohd Tahir, Audu, Buba, Tumala, Mohammed Musa
• Format: Article
• Language: English
• Published: Elsevier 2016
• Subjects: QA1-939 Mathematics
• 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

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.