A Comparison of LSTMs and Attention Mechanisms for Forecasting Financial Time Series

18 Dec 2018Thomas HollisAntoine ViscardiSeung Eun Yi

While LSTMs show increasingly promising results for forecasting Financial Time Series (FTS), this paper seeks to assess if attention mechanisms can further improve performance. The hypothesis is that attention can help prevent long-term dependencies experienced by LSTM models... (read more)

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