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Comparative multivariate forecast performance for the G7 Stock Markets: VECM Models vs deep learning LSTM neural networks

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Comparative multivariate forecast performance for the G7 Stock Markets: VECM Models vs deep learning LSTM neural networks

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Mendes, D.; Ferreira, NR.; Mendes, V. (2020). Comparative multivariate forecast performance for the G7 Stock Markets: VECM Models vs deep learning LSTM neural networks. Editorial Universitat Politècnica de València. 163-171. https://doi.org/10.4995/CARMA2020.2020.11616

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/149596

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Title: Comparative multivariate forecast performance for the G7 Stock Markets: VECM Models vs deep learning LSTM neural networks
Author: Mendes, Diana Ferreira, Nuno Rafael Mendes, Vivaldo
Issued date:
Abstract:
[EN] The prediction of stock prices dynamics is a challenging task since these kind of financial datasets are characterized by irregular fluctuations, nonlinear patterns and high uncertainty dynamic changes.The deep neural ...[+]
Subjects: Web data , Internet data , Big data , Qca , Pls , Sem , Conference , Stock markets , Multivariate forecasting , VECM , LSTM
Copyrigths: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
ISBN: 9788490488324
DOI: 10.4995/CARMA2020.2020.11616
Publisher:
Editorial Universitat Politècnica de València
Publisher version: http://ocs.editorial.upv.es/index.php/CARMA/CARMA2020/paper/view/11616
Conference name: CARMA 2020 - 3rd International Conference on Advanced Research Methods and Analytics
Conference place: Valencia, Spain
Conference date: Julio 08-09,2020
Type: Capítulo de libro Comunicación en congreso

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