EVALUATING BEST GARCH MODEL FOR FORECASTING STOCK RETURNS OF EMERGING MARKETS IN AFRICA
The emerging market economies are fast improving in terms of real sector and financial sector growth. Due to the potentials in these economies, there have been influx of investors in these stock markets. The aim of this paper is to find best GARCH model for forecasting stock returns of emerging economies. This study adopted daily data (14/04/2010-08/06/2021) for ten emerging market economies. They are Tunisia, Botswana, Egypt, Kenya, Nigeria, Namibia, Mauritius, Sudan, Morocco and Malaysia. The GARCH type models were adopted. First, it was observed the best model for forecasting volatility in Tunisia bank, Malaysia breweries, Nigeria (MTN), Nigeria (breweries) stock market is exponential GARCH (eGARCH). Where sGARCH is applicable as in the case of Egypt, Kenya, and Sudan stock market, the market volatility in these markets does not react differently to market news. For Egypt, Kenya, and Sudan stock market, the standard GARCH (sGARCH) performs best. The emerging markets namely, Tunisia Bank, Nigeria Breweries, Nigeria MTN, Malaysia Building Society, Namibia Breweries where eGARCH and gjrGARCH are applicable implies their stock market returns react differently to market news relating to them. These findings have policy implications for investors in these respective economies. The asymmetric GARCH models highlighted should be used to forecast stock returns of Tunisia bank, Malaysia building society, Nigeria MTN and breweries as well as Namibia breweries.Amongst others, the study so recommend that investors in these market particularly those in the equity market where volatility decay slowly and the market where volatility responds asymmetrically to be watchful as these could pose significant threat to their market portfolio.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-05-26
- DOI
- https://doi.org/10.5281/zenodo.15520727
- Primary Topic
- Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Type
- article
- Field-Weighted Citation Impact
- 0.00