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Machine learning advances for time series forecasting
Masini, Ricardo P.; Medeiros, Marcelo C.; Mendes, Eduardo F. - 2020
series forecasting. We consider both linear and nonlinear alternatives. Among the linear methods we pay special attention to …
Persistent link: https://www.econbiz.de/10012390030
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Machine learning advances for time series forecasting
Masini, Ricardo P.; Medeiros, Marcelo C.; Mendes, Eduardo F. - In: Journal of economic surveys 37 (2023) 1, pp. 76-111
Persistent link: https://www.econbiz.de/10014287800
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Testing for Spurious Long Memory : A Monte Carlo Comparison with an Application to Credit Default Swaps
Leccadito, Arturo - 2010
A common feature of financial time series is their strong persistence. Yet, long memory may just be the spurious effect of either structural breaks or slow switching regimes. So far, five testing procedures have been proposed to distinguish between true and spurious long memory. The tests are...
Persistent link: https://www.econbiz.de/10013146725
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A solution for M5 Forecasting-uncertainty : Hybrid gradient boosting and autoregressive recurrent neural network for quantile estimation
Chiew, Ernest; Choong, Shin Siang - In: International journal of forecasting 38 (2022) 4, pp. 1442-1447
Persistent link: https://www.econbiz.de/10014381105
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A parallel-series hybridization of seasonal intelligent based statistical model for demand forecasting
Bahrami, Maryam; Khashei, Mehdi; Amindoust, Atefeh - In: Journal of modelling in management 17 (2022) 4, pp. 1126-1143
Persistent link: https://www.econbiz.de/10014334156
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A Bayesian estimation approach of random switching exponential smoothing with application to credit forecast
Wang, Renhe; Wang, Tong; Qian, Zhiyong; Hu, Shulan - In: Finance research letters 58 (2023) 3, pp. 1-9
Persistent link: https://www.econbiz.de/10014631562
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Forecast accuracy of the linear and nonlinear autoregressive models in macroeconomic modeling
Taiebnia, Ali; Mohammadi, Shapour - In: Journal of forecasting 42 (2023) 8, pp. 2045-2062
Persistent link: https://www.econbiz.de/10014432847
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Predicting stock return and volatility with machine learning and econometric models : a comparative case study of the Baltic stock market
Nõu, Anders; Lapitskaya, Darya; Eratalay, M. Hakan; … - In: International journal of computational economics and … 13 (2023) 4, pp. 446-489
Persistent link: https://www.econbiz.de/10014439728
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NNPF : Neural Network Particle Filter for time series data
Peerlings, Dewi; Brakel, Jan A. van den; Baştürk, Nalan - 2024
Persistent link: https://www.econbiz.de/10014524761