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Machine learning with parallel neural networks for analyzing and forecasting electricity demand

Chen, Yi-Ting; Sun, Edward W.; Lin, Yi-Bing - In: Computational economics 56 (2020) 2, pp. 569-597

Persistent link: https://www.econbiz.de/10012272048

Semiparametric quantile averaging in the presence of high-dimensional predictors

Gooijer, Jan G. de; Zerom Godefay, Dawit - In: International journal of forecasting 35 (2019) 3, pp. 891-909

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Demystifying the Meese-Rogoff puzzle : structural breaks or measures of forecasting accuracy?

Burns, Kelly; Moosa, Imad A. - In: Applied economics 49 (2017) 48, pp. 4897-4910

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The random walk as a forecasting benchmark : drift or no drift?

Moosa, Imad A.; Burns, Kelly - In: Applied economics 48 (2016) 43/45, pp. 4131-4142

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Jump detection and noise separation by a singular wavelet method for predictive analytics of high-frequency data

Chen, Yi-Ting; Lai, Wan-Ni; Sun, Edward W. - In: Computational economics 54 (2019) 2, pp. 809-844

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Asymmetries in conditional mean and variance : modelling stock returns by asMA-asQGARCH

Brännäs, Kurt; Gooijer, Jan G. de - 2000

variancefunctions. In a genuine out-of-sample forecasting experiment theperformance of the best fitted asMA-asQGARCH model is compared … topure asMA and no-change forecasts. This is done both in terms ofconditional mean forecasting as well as in terms of risk … forecasting. …

Persistent link: https://www.econbiz.de/10011303289