Volatility forecasting with the wavelet transformation algorithm GARCH model: Evidence from African stock markets - Ismail, Mohd Tahir; Audu, Buba; Tumala, Mohammed Musa (Elsevier, 2016)
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.