In dieser Arbeit wird die Eignung des Instrumentariums der neuronalen Netze, im Konkreten der autoregressiven Neuronale-Netz-Modelle (ARNN), zur Modellierung und Prognose von makroökonomischen Zeitreihen untersucht und mit jenen der autoregressiven (AR) und autoregressiven...

Using Gretl, I apply ARMA, Vector ARMA, VAR, state-space model with a Kalman filter, transfer-function and intervention models, unit root tests, cointegration test, volatility models (ARCH, GARCH, ARCH-M, GARCH-M, Taylor-Schwert GARCH, GJR, TARCH, NARCH, APARCH, EGARCH) to analyze quarterly time...

Recently, Donaldson and Kamstra (1997) proposed a class of NN-GARCH models which are extended to a class of NN-GARCH family by Bildirici and Ersin (2009). The study aims to analyze the nonlinear behavior and leptokurtic distribution in petrol prices by utilizing a newly developed family of...

The English version of this paper can be found at: "http://ssrn.com/abstract=2227747" http://ssrn.com/abstract=2227747Çalışma, temel GARCH modelinin Destek Vektör Makinesi ve Yapay Sinir Ağları ile iyileştirilmiş modellerin incelenerek GARCH modelinin tahmin performansının...

I develop methods that produce consistent estimates of the Vasicek-Basel IRB (VAIRB) credit risk model parameters. I apply these methods to Moody's data on corporate defaults over the period 1920–2008 and assess the model fit and construct hypothesis tests using bootstrap methods. The results...