conditional heteroscedasticity (GARCH) model. In this test, the training samples, testing samples, and kernel functions of the … experiments were performed using the GARCH model, and the accuracies of these two approaches were compared. Findings: Compared … with GARCH, GMDH's accuracy is much higher, indicating that the machine learning approach can provide a highly accurate …

, such as Multivariate DCC-GARCH and Continuous Wavelet Transform (CWT) to test the research objective. The period of …

of ARCH effect has been tried to predict with conditional variance models such as ARCH (1), ARCH (2), ARCH (3), GARCH (1 …,1), GARCH (1,2), GARCH (1,3), GARCH (2,1), GARCH (2,2), EGARCH (1,1) and EGARCH (1,2). While the obtained findings indicate that … the best model is in the direction of GARCH (1,1) according to Akaike info criterion, it was found that GARCH (1,1) model …

investment decisions. The used risk attribution quantification models GARCH (1.1), EGARCH (1.1), GARCH-M (1.1) and TGARCH (1 … concentration of investment funds (in Bulgaria) through the testing of complex, analytical and specialized models from the GARCH … models GARCH, EGARCH, GARCH-M and TGARCH with specification (1.1). The research covers the net balance sheet value of forty …

the best fitting model among SGARCH, EGARCH and GJR-GARCH. In a bid to account for the dynamic and persistent nature of …