المقارنة بين نماذج EGARCH والشبكات العصبية الاصطناعية في قياس أثر المخاطر المنتظمة على المؤشر العام لسوق الأوراق المالية في مصر | ||||
| The Egyptian Statistical Journal | ||||
| Article 9, Volume 58, Issue 2, December 2014, Page 71-88 PDF (9.4 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/esju.2014.314452 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| ماهر احمد علي | ||||
| كلية الدراسات العليا للبحوث الاحصائية | ||||
| Abstract | ||||
| The main objective of this paper is to make a comparison between an EGARCH models and artificial neural networks approach in measuring the impact of systematic risk on the stock market index in Egypt. The main finding proved that the artificial neural networks more goodness of fit of the monthly returns of stock market index EGX100, than EGARCH models in terms of fit measures; RMSE, MAPE, MAE, thiel inequality, and R2 | ||||
| Keywords | ||||
| EGARCH; Neural Networks; Systematic Risks; Stock Market Index EGX100 | ||||
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