| |
original article |
Journal |
Date |
Title |
Authors All Authors |
| 1 |
[GO] |
African Journal of Applied Statistics |
2025―Oct―29 |
Deep learning-based methods for predicting COVID-19: A critical review |
Fréjus Stéphane Tinhoun, Têlé Jonas Doumate, Romain Glèlè Kakaï |
| 2 |
[GO] |
African Journal of Applied Statistics |
2021―Oct―26 |
Short-term prediction model for daily COVID-19 reported positive cases in Senegal |
Aba Diop, Abdourahmane Ndao, Cheikh Tidiane Seck, Ibrahima Faye |
| 3 |
[GO] |
African Journal of Applied Statistics |
2021―Aug―12 |
Short-term prediction model for daily COVID-19 reported positive cases in Senegal |
Aba Diop, Abdourahmane Ndao, Cheikh Tidiane Seck, Ibrahima Faye |
| 4 |
[GO] |
African Journal of Applied Statistics |
2021―Jul―02 |
The spread of the coronavirus is putting a strain on financial markets and the resulting stock market volatility is causing huge problems for investors. Volatility in the U.S. market has returned to levels not seen since the 2011 sovereign debt crisis. It is already clear that this volatility has had a negative effect on the economy. In this study, we introduce a regime-switching GJR-GARCH modelwith a stable distribution to investigate the predictive power of the S&P 500 index volatility to VaR estimation. The results of VaR backtesting at a 5% risk level confirm that the model performs better and is a useful tool for the risk manager and financial regulator |
Gado SEMA, Mamadou Abdoulaye Konté, Abdou Kâ Diongue |
| 5 |
[GO] |
African Journal of Applied Statistics |
2020―Dec―28 |
A note on Covid-19 Statistics, Strange trend and Forecasting of Total Cases in the most Infected African Countries: An ARIMA and Fuzzy Time Series Approaches |
Chellai Fatih, Ahmed Hamimes, Pradeep Mishra |
