Stock Predicting based on LSTM and ARIMA

Huizi Qian ()
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Huizi Qian: University of Chinese Academy of Social Sciences, Department of Industrial Economics

A chapter in Proceedings of the 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022), 2022, pp 485-490 from Springer

Abstract: Abstract With the application of artificial intelligence algorithm in the financial field, it soon becomes an interesting issue and a research hotspot to predict stock price. In this paper, LSTM and ARIMA models are adopted to explore the attracting stock price prediction. Besides, forecasting accuracy is comprehensively compared by several statistic indicators, i.e., MSE, MAE and RMSE. Based on the historical closing price collected from the Yahoo Finance, the above models are constructed. The prediction results show that the LSTM algorithm has a smaller MSE, MAE and RMSE, than the alternative ARIMA. The results in this paper may be beneficial to investors in the capital market when forecasting the future prices.

Keywords: Stock price; Predicting; LSTM; ARIMA (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-036-7_72

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DOI: 10.2991/978-94-6463-036-7_72

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