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Discussion of the paper "Forecasting performance of three automated modeling techniques during the economic crisis 2007 - 2009" by A. Kock and T. Teräsvirta

Dubois, Eric - In: International journal of forecasting 30 (2014) 3, pp. 632-634

Persistent link: https://www.econbiz.de/10010514784

Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009

Kock, Anders Bredahl; Teräsvirta, Timo - In: International Journal of Forecasting 30 (2014) 3, pp. 616-631

’s QuickNet, but we also consider Autometrics, which is well known to time series econometricians, and the Marginal Bridge …

Persistent link: https://www.econbiz.de/10011051442

Chapter 9 Approximate Nonlinear Forecasting Methods

White, Halbert - 2006

(QuickNet) that achieves the benefits of using a forecasting model that is nonlinear in the predictors while avoiding or …

Persistent link: https://www.econbiz.de/10014023697

Evaluating the combined forecasts of the dynamic factor model and the artificial neural network model using linear and nonlinear combining methods

Babikir, Ali; Mwambi, Henry - In: Empirical economics : a journal of the Institute for … 51 (2016) 4, pp. 1541-1556

Persistent link: https://www.econbiz.de/10011661817

Intelligent forecasting of economic growth for developing economies

Chuku, Chuku Agbai; Simpasa, Anthony Musonda; Oduor, Jacob - In: International economics : a journal published by CEPII … 159 (2019), pp. 74-93

Persistent link: https://www.econbiz.de/10012318821

Forecasting economic activity using a neural network in uncertain times : Monte Carlo evidence and application to the German GDP

Holtemöller, Oliver; Kozyrev, Boris - Leibniz-Institut für Wirtschaftsforschung Halle - 2024

In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an...

Persistent link: https://www.econbiz.de/10014496850