Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
387168 | Expert Systems with Applications | 2009 | 8 Pages |
Abstract
In the study, we discussed the ARCH/GARCH family models and enhanced them with artificial neural networks to evaluate the volatility of daily returns for 23.10.1987–22.02.2008 period in Istanbul Stock Exchange. We proposed ANN-APGARCH model to increase the forecasting performance of APGARCH model. The ANN-extended versions of the obtained GARCH models improved forecast results. It is noteworthy that daily returns in the ISE show strong volatility clustering, asymmetry and nonlinearity characteristics.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Melike Bildirici, Özgür Ömer Ersin,