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Published on 27 September 2024
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Deng,M. (2024). Stock prediction based on HMM and LSTM model and model selection using SVM. Theoretical and Natural Science,52,81-89.
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Stock prediction based on HMM and LSTM model and model selection using SVM

Moxun Deng *,1,
  • 1 Leicester International Institute, Dalian University of Technology, Dalian, 116085, China

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2753-8818/52/2024CH0138

Abstract

Su G and Deng F, 2006 Model Selection for Support Vector Regression, Science and Technology Bulletin, 22(2), 5.Su G and Deng F, 2006 Model Selection for Support Vector Regression, Science and Technology Bulletin, 22(2), 5.Su G and Deng F, 2006 Model Selection for Support Vector Regression, Science and Technology Bulletin, 22(2), 5.

Keywords

Stock prices, Hidden Markov Model, Long Short-Term Memory, Support Vector Machine

[1]. Morck, et al. 2000 The information content of stock markets: why do emerging markets have synchronous stock price movement?, Journal of Financial Economics.

[2]. Wen F, et al. 2014 Research on the Impact of Investor Emotional Characteristics on Stock Price Behavior, Journal of Management Science, 3, 60-69.

[3]. Hong H, et al. 2008 The Only Game in Town: Stock-Price Consequences of Local Bias. Journal of Financial Economics, 1, 20-37.

[4]. Song Q and Yu S, 2002 On the Relationship between Monetary Policy and Stock Market, Wuhan Finance.

[5]. Hassan M R and Nath B, 2005 Stock market forecasting using hidden Markov model: a new approach, 5th International Conference on Intelligent Systems Design and Applications, 192-196.

[6]. Nguyet N, 2018 Stock Price Prediction using Hidden Markov Model, Int. J. Financial Stud., 6(2).

[7]. Su G and Deng F, 2006 Model Selection for Support Vector Regression, Science and Technology Bulletin, 22(2), 5.

[8]. Hassan M R, et al. 2007 A fusion model of HMM, ANN and GA for stock market forecasting. Expert systems with Applications, 33(1), 171-180.

[9]. Nelson D M Q, et al. 2017 Stock market's price movement prediction with LSTM neural networks, 2017 International joint conference on neural networks (IJCNN) IEEE, 1419-1426.

Cite this article

Deng,M. (2024). Stock prediction based on HMM and LSTM model and model selection using SVM. Theoretical and Natural Science,52,81-89.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of CONF-MPCS 2024 Workshop: Quantum Machine Learning: Bridging Quantum Physics and Computational Simulations

Conference website: https://2024.confmpcs.org/
ISBN:978-1-83558-621-1(Print) / 978-1-83558-622-8(Online)
Conference date: 9 August 2024
Editor:Anil Fernando, Marwan Omar
Series: Theoretical and Natural Science
Volume number: Vol.52
ISSN:2753-8818(Print) / 2753-8826(Online)

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