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Modeling and forecasting short-term electricity load : a comparison of methods with an application to Brazilian data
Soares, Lacir J.; Medeiros, Marcelo C. - In: International journal of forecasting 24 (2008) 4, pp. 630-644
Persistent link: https://www.econbiz.de/10003808337
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Asymmetric effects and long memory in the volatility of Dow Jones stocks
Scharth, Marcel; Medeiros, Marcelo C. - In: International journal of forecasting 25 (2009) 2, pp. 304-327
Persistent link: https://www.econbiz.de/10003870060
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Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series : a re-examination
Teräsvirta, Timo; Dijk, Dick van; Medeiros, Marcelo C. - In: International journal of forecasting 21 (2005) 4, pp. 755-774
Persistent link: https://www.econbiz.de/10003150707
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Comments on "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series : a re-examination
Novales, Alfonso - In: International journal of forecasting 21 (2005) 4, pp. 775-780
Persistent link: https://www.econbiz.de/10003150708
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Real-time inflation forecasting with high-dimensional models : the case of Brazil
Garcia, Márcio Gomes Pinto; Medeiros, Marcelo C.; … - In: International journal of forecasting 33 (2017) 3, pp. 679-693
Persistent link: https://www.econbiz.de/10011746198
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Short-term Covid-19 forecast for latecomers
Medeiros, Marcelo C.; Street, Alexandre; Valladão, Davi; … - In: International journal of forecasting 38 (2022) 2, pp. 467-488
Persistent link: https://www.econbiz.de/10013348609
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Reply: [Comments on "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series : a re-examination]
Teräsvirta, Timo; Dijk, Dick van; Medeiros, Marcelo C. - In: International journal of forecasting 21 (2005) 4, pp. 781-783
Persistent link: https://www.econbiz.de/10003150710
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Forecasting the Brazilian yield curve using forward-looking variables
Vieira, Fausto; Fernandes, Marcelo; Chague, Fernando - In: International journal of forecasting 33 (2017) 1, pp. 121-131
Persistent link: https://www.econbiz.de/10011754690