Back to Article
Nigeria Exchange Rate Volatility: A Comparative Study of Recurrent Neural Network LSTM and Exponential Generalized Autoregressive Conditional Heteroskedasticity Models
Journal of Artificial Intelligence and Big Data
| Vol 4, Issue 2
Table 3. EGARCH (1,1) models Fitted for Euro, Pound Sterling and US Dollars.
| Particulars | Euro | Pound Sterling | US Dollars |
| Variable | Coef. (p-value) | Coef. (p-value) | Coef. (p-value) |
| Constant | 4.634 (0.000) | 11.341 (0.000) | 7.523 (0.000) |
| 1 st Lag Order | -0.765 (0.000) | -2.112 (0.000) | 3.244 (0.000) |
| 2nd Lag Order | -0.513 (0.000) | -1.763 (0.000) | -2.332 (0.000) |
| 3rd Lag Order | -0.582 (0.000) | -0.352 (0.000) | 3.774 (0.000) |
| 4th Lag Order | -0.342 (0.000) | -0.996 (0.000) | 3.798 (0.000) |
| Performance Criteria | |||
| R-squared | 0.812191 | 0.820555 | 0.887292 |
| Loglikelihood | -1387.898 | -1313.194 | -1230.568 |
| Durbin-Watson | 2.024220 | 2.033607 | 2.018676 |
| AIC | 10.66588 | 10.09344 | 9.460294 |
| SIC | 10.72051 | 10.14807 | 9.514922 |
Note: AIC is the Akaike info criterion and SC is the Schwarz criterion