Short-Term Price Trend Forecast Based on LSTM Neural Network

A Study Based on Chinese Stock Market Data on Liquor Stocks

DOI

10.2991/978-94-6463-036-7_30How to use a DOI?

Keywords

Liquor Industry; Deep Learning; Neural Networks; Price Trend Forecasting

ABSTRACT

With the improvement and application of machine learning and enormous information innovation, securities market forecast has pulled in broad consideration within the business and the scholarly world. This ponders employments person stock information of listed liquor companies in China to investigate the impact of LSTM neural organize on liquor stock time arrangement forecast. The test takes every day exchanging information of Moutai and Wuliangye Yibin from March 31, 2002, to March 31, 2022, as the free variable to foresee the closing cost. The test comes about to appear that LSTM neural organize demonstrate has tall precision and steady forecast impact on cost drift forecast. It has superior prescient esteem for the stocks with little showcase esteem of Chinese liquor, which is helpful for speculators to create choices.

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  - Zixuan Wang
PY  - 2022
DA  - 2022/12/31
TI  - Short-Term Price Trend Forecast Based on LSTM Neural Network
BT  - Proceedings of the 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022)
PB  - Atlantis Press
SP  - 203
EP  - 209
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-036-7_30
DO  - 10.2991/978-94-6463-036-7_30
ID  - Wang2022
ER  -