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Predicting the determinants of mobile payment acceptance : a hybrid SEM-neural network approach

Liébana-Cabanillas, Francisco; Marinkovic, Veljko; … - In: Technological forecasting & social change : an … 129 (2018), pp. 117-130

Persistent link: https://www.econbiz.de/10011958039

A multi-analytical approach to peer-to-peer mobile payment acceptance prediction

Kalinić, Zoran; Marinkovic, Veljko; Molinillo, Sebastián - In: Journal of retailing and consumer services 49 (2019), pp. 143-153

Persistent link: https://www.econbiz.de/10012025841

Nowcasting economic activity with electronic payments data : a predictive modeling approach

León, Carlos; Ortega, Fabio - In: Revista de economía del Rosario 21 (2018) 2, pp. 381-407

Persistent link: https://www.econbiz.de/10012029993

Nowcasting economic activity with electronic payments data : a predictive modeling approach

León, Carlos; Ortega, Fabio - 2018

Persistent link: https://www.econbiz.de/10011870442

LASSO-based high-frequency return predictors for profitable Bitcoin investment

Huang, Weige; Gao, Xiang - In: Applied economics letters 29 (2022) 12, pp. 1079-1083

Persistent link: https://www.econbiz.de/10013412041

Next-day Bitcoin price forecast

Munim, Ziaul Haque; Shakil, Mohammad Hassan; Alon, Ilan - In: Journal of risk and financial management : JRFM 12 (2019) 2/103, pp. 1-15

This study analyzes forecasts of Bitcoin price using the autoregressive integrated moving average (ARIMA) and neural network autoregression (NNAR) models. Employing the static forecast approach, we forecast next-day Bitcoin price both with and without re-estimation of the forecast model for each...

Persistent link: https://www.econbiz.de/10012021953