Parameter Optimisation of LSTM Models in Stock Price Prediction | IEEE Conference Publication | IEEE Xplore
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Parameter Optimisation of LSTM Models in Stock Price Prediction

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Pi Rey Low; Eric Sakk
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Abstract:

This study investigates the forecasting accuracies of Long Short-Term Memory models with different architectures and sheds light on the optimal combination of parameters ...Show More

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Abstract:

This study investigates the forecasting accuracies of Long Short-Term Memory models with different architectures and sheds light on the optimal combination of parameters when forecasting stock prices for the S&P500 fund.
Published in: TENCON 2022 - 2022 IEEE Region 10 Conference (TENCON)
Date of Conference: 01-04 November 2022
Date Added to IEEE Xplore: 20 December 2022
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ISSN Information:

DOI: 10.1109/TENCON55691.2022.9978045
Conference Location: Hong Kong, Hong Kong
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