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  • 标题:Volatility forecasting with the wavelet transformation algorithm GARCH model: Evidence from African stock markets
  • 本地全文:下载
  • 作者:Mohd Tahir Ismail ; Mohd Tahir Ismail ; Buba Audu
  • 期刊名称:The Journal of Finance and Data Science
  • 印刷版ISSN:2405-9188
  • 出版年度:2016
  • 卷号:2
  • 期号:2
  • 页码:125-135
  • DOI:10.1016/j.jfds.2016.09.002
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Abstract 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.
  • 关键词:Volatility;Asset returns;MODWT;GARCH
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