Stock Predicting based on LSTM and ARIMA

DOI

10.2991/978-94-6463-036-7_72How to use a DOI?

Keywords

Stock price; Predicting; LSTM; ARIMA

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.

Copyright

© 2022 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Huizi Qian
PY  - 2022
DA  - 2022/12/31
TI  - Stock Predicting based on LSTM and ARIMA
BT  - Proceedings of the 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022)
PB  - Atlantis Press
SP  - 485
EP  - 490
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-036-7_72
DO  - 10.2991/978-94-6463-036-7_72
ID  - Qian2022
ER  -