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Using wavelets for time series forecasting: Does it pay off?

Schlüter, Stephan; Deuschle, Carola - 2010

By means of wavelet transform a time series can be decomposed into a time dependent sum of frequency components. As a result we are able to capture seasonalities with time-varying period and intensity, which nourishes the belief that incorporating the wavelet transform in existing forecasting...

Persistent link: https://www.econbiz.de/10010300727

Software implementation of realtime discrete wavelet transform algorithm with filter banks

Bogdanovs, Nikolajs; Grabs, Elans; Petersons, Ernests - In: International journal of information systems in the … 8 (2016) 2, pp. 70-86

Persistent link: https://www.econbiz.de/10011493945

Does investor sentiment differently affect stocks in different sectors? : evidence from China

Niu, Hongli; Lu, Yao; Wang, Weiqing - In: International journal of emerging markets 18 (2023) 9, pp. 3224-3244

Persistent link: https://www.econbiz.de/10014452289

Commodities price cycles and their interdependence with equity markets

Boako, Gideon; Alagidede, Imhotep Paul - 2021

Persistent link: https://www.econbiz.de/10012631215

Dynamic spillover effect between oil prices and economic policy uncertainty in bric countries : a wavelet-based approach

Chen, Xiuwen; Sun, Xiaolei; Wang, Jun - In: Emerging markets, finance and trade : EMFT 55 (2019) 12, pp. 2703-2717

Persistent link: https://www.econbiz.de/10012211021

Commodities price cycles and their interdependence with equity markets

Boako, Gideon; Alagidede, Imhotep Paul; Sjo, Bo; Uddin, … - In: Energy economics 91 (2020), pp. 1-26

Persistent link: https://www.econbiz.de/10012518586

Multiscale extreme risk spillovers among the Chinese mainland, Hong Kong, and London stock markets : comparing the impacts of three Stock Connect programs

Yao, Yinhong; Li, Jingyu; Chen, Wei - In: International review of economics & finance : IREF 89 (2024) 1, pp. 1217-1233

Persistent link: https://www.econbiz.de/10014446620