May 15, 2024, 4:42 a.m. | Ali Mohammadjafari

cs.LG updates on arXiv.org arxiv.org

arXiv:2405.08089v1 Announce Type: cross
Abstract: Prediction of stock prices has been a crucial and challenging task, especially in the case of highly volatile digital currencies such as Bitcoin. This research examineS the potential of using neural network models, namely LSTMs and GRUs, to forecast Bitcoin's price movements. We employ five-fold cross-validation to enhance generalization and utilize L2 regularization to reduce overfitting and noise. Our study demonstrates that the GRUs models offer better accuracy than LSTMs model for predicting Bitcoin's price. …

abstract arxiv bitcoin case comparative study cs.lg currencies digital five forecast movements network neural network prediction price q-fin.st research stock study type validation

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