[引用][C] Approach Advancing Stock Market Forecasting with Joint RMSE Loss LSTM-CNN Model
Approach Advancing Stock Market Forecasting with Joint RMSE Loss LSTM-CNN Model
M Kiran Kumar, J Chandra Patni… - … and Noise Letters, 2024 - ui.adsabs.harvard.edu
The intricacies and dynamism of financial markets pose challenges to models seeking to
comprehensively capture the multitude of factors influencing stock price movements. As
such, there remains room for improvement in forecasting accuracy. In response, we
introduce a novel approach that unifies the Root Mean Square Error (RMSE), loss functions
of Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN). By
concurrently optimizing their RMSE loss functions, our novel approach takes use of the …
comprehensively capture the multitude of factors influencing stock price movements. As
such, there remains room for improvement in forecasting accuracy. In response, we
introduce a novel approach that unifies the Root Mean Square Error (RMSE), loss functions
of Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN). By
concurrently optimizing their RMSE loss functions, our novel approach takes use of the …
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