Fitting the Nigeria Stock Market Return Series Using GARCH Models
| العنوان: | Fitting the Nigeria Stock Market Return Series Using GARCH Models |
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| المؤلفون: | Umar Usman, H. M. Auwal, M. A. Abdulmuhyi |
| المصدر: | Theoretical Economics Letters. :2159-2176 |
| بيانات النشر: | Scientific Research Publishing, Inc., 2017. |
| سنة النشر: | 2017 |
| مصطلحات موضوعية: | 050208 finance, Autoregressive conditional heteroskedasticity, 05 social sciences, Bayesian probability, Log likelihood, Stock market index, 0502 economics and business, Econometrics, Stock market, 050207 economics, Volatility (finance), Akaike information criterion, Mathematics, Training period |
| الوصف: | This study investigated the performance of eleven competing time series GARCH models for fitting the rate of returns data, monthly observations on the index returns series of the market over the period of January 1996 to December 2015 was used. From the results obtained from the Log Likelihood (Log L), Schwarzs Bayesian Criterion (SBC) and the Akaike Information Criterion (AIC) values it was found that the models identified was not the same for the two periods (Training and Testing period) that is for Training period were CGARCH (1,1) and EGARCH (1,1) while for Testing period were ARCH (1) and GARCH (2,1). The two extreme classes of models are identified to represent the best and the worst groups respectively. The overall effect of this will tend to increase the volatility of the market returns. The paper therefore recommended that the Nigeria government should as a matter of urgency take appropriate positive measures through the security and exchange commission to regulate the market volatility so that the provided market index could be safely used as predictive index for measuring the performance of the firms and as a guide for investment purpose. |
| تدمد: | 2162-2086 2162-2078 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::63427ae57c4925967df07ad8f5adbbd9 https://doi.org/10.4236/tel.2017.77147 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi...........63427ae57c4925967df07ad8f5adbbd9 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 21622086 21622078 |
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