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Nowcasting GDP growth for small open economies with a mixed-frequency structural model

Yau, Ruey; Hueng, C. James - In: Computational economics 54 (2019) 1, pp. 177-198

Persistent link: https://www.econbiz.de/10012134110

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

Persistent link: https://www.econbiz.de/10012134380

Forecasting inflation in Tunisia during instability using dynamic factors model : a two-step based procedure based on Kalman filter

Ammouri, Bilel; Toumi, Hassen; Issaoui, Fakhri; … - In: International journal of computational economics and … 9 (2019) 1/2, pp. 49-83

Persistent link: https://www.econbiz.de/10012021571

Fractal investigation and maximal overlap discrete wavelet transformation (MODWT)-based machine learning framework for forecasting exchange rates

Ghosh, Indranil; Chaudhuri, Tamal D. - In: Studies in microeconomics 5 (2017) 2, pp. 105-131

Persistent link: https://www.econbiz.de/10012023833

Forecasting structural change and fat-tailed events in Australian macroeconomic variables

Cross, Jamie; Poon, Aubrey - In: Economic modelling 58 (2016), pp. 34-51

Persistent link: https://www.econbiz.de/10011647028

Can Google search data help predict macroeconomic series?

Niesert, Robin; Oorschot, Jochem; Veldhuisen, Chris; … - 2019

We use Google search data with the aim of predicting unemployment, CPI and consumer confidence for the US, UK, Canada, Germany and Japan. Google search queries have previously proven valuable in predicting macroeconomic variables in an in-sample context. To our knowledge, the more challenging...

Persistent link: https://www.econbiz.de/10011987495

Multifractal behavior in precious metals : wavelet coherency and forecasting by VARIMA and V-FARIMA models

Doğangün, Itir; Ünal, Gazanfer - In: Annals of financial economics 14 (2019) 2, pp. 1-12

Persistent link: https://www.econbiz.de/10012030827

Forecasting realized variance measures using time-varying coefficient models

Bekierman, Jeremias; Manner, Hans - In: International journal of forecasting 34 (2018) 2, pp. 276-287

Persistent link: https://www.econbiz.de/10012030902

What do professional forecasters actually predict?

Nibbering, Didier; Paap, Richard; Wel, Michel van der - In: International journal of forecasting 34 (2018) 2, pp. 288-311

Persistent link: https://www.econbiz.de/10012030904

Inversion copulas from nonlinear state space models with an application to inflation forecasting

Smith, Michael S.; Maneesoonthorn, Worapree - In: International journal of forecasting 34 (2018) 3, pp. 389-407

Persistent link: https://www.econbiz.de/10012030987

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