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Reservoir computing vs. neural networks in financial forecasting

Georgopoulos, Spyros P.; Tziatzios, Panagiotis; … - In: International journal of computational economics and … 13 (2023) 1, pp. 1-22

Persistent link: https://www.econbiz.de/10014307624

Novel Financial Applications of Machine Learning and Deep Learning : Algorithms, Product Modeling, and Applications

Abedin, Mohammad Zoynul (ed.); Hájek, Petr (ed.) - 2023

financial product modeling, which aims to advance the model performance and minimize risk and uncertainty. It provides both …

Persistent link: https://www.econbiz.de/10014226726

A novel hybrid deep learning method for accurate exchange rate prediction

Iqbal, Farhat; Koutmos, Dimitrios; Zaki, Eman Ahmed … - In: Risks : open access journal 12 (2024) 9, pp. 1-20

results in enhancing predictive accuracy. Motivated by the growing size of the FX market, as well as advancements in ML, we … findings demonstrate that the MVO-BiGRU model can successfully avoid overfitting and achieve the highest accuracy in out …

Persistent link: https://www.econbiz.de/10015066311

Predicting retirement and social security claiming decisions using machine learning

Kwon, Alexander; Maliar, Lilia - 2024

Persistent link: https://www.econbiz.de/10014564329

Use of prediction bias in active learning and its application to large variable annuity : Portfolios

Gweon, Hyukjun; Li, Shu; Xu, Yangxuan - In: Risks : open access journal 12 (2024) 6, pp. 1-14

Given the computational challenges associated with valuing large variable annuity (VA) portfolios, a variety of data mining frameworks, including metamodeling and active learning, have been proposed in recent years. Active learning, a promising alternative to metamodeling, enhances the...

Persistent link: https://www.econbiz.de/10014636846