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CDS approximation accuracy improvement with cart and random forest algorithms based on a time span including the COVID-19 pandemic period

Mercadier, Mathieu - In: Recent trends in financial engineering : towards more …, (pp. 39-63). 2023

Persistent link: https://www.econbiz.de/10013462187

Adaptive evolutionary neural networks for forecasting and trading without a data-snooping bias

Sermpinis, Georgios; Verousis, Thanos; Theofilatos, … - In: Journal of forecasting 35 (2016) 1, pp. 1-12

Persistent link: https://www.econbiz.de/10011417657

Evaluating the performance of metaheuristic based artificial neural networks for cryptocurrency forecasting

Behera, Sudersan; Nayak, Sarat; Kumar, A. V. S. Pavan - In: Computational economics 64 (2024) 2, pp. 1219-1258

Persistent link: https://www.econbiz.de/10015078086

Expert aggregation for financial forecasting

Remlinger, Carl; Alasseur, Clémence; Brière, Marie; … - In: The Journal of finance and data science : JFDS 9 (2023), pp. 1-21

Machine learning algorithms dedicated to financial time series forecasting have gained a lot of interest. But choosing between several algorithms can be challenging, as their estimation accuracy may be unstable over time. Online aggregation of experts combine the forecasts of a finite set of...

Persistent link: https://www.econbiz.de/10014514016