Evaluation of Stock Market Risk Model Based on Random Forest + Two-Way LSTM

DOI

10.2991/978-94-6463-198-2_95How to use a DOI?

Keywords

Stock trading; Random forest; Bidirectional LSTM; Securities trading; Risk identification and evaluation

Abstract

In view of the fact that the traditional risk evaluation model has the problem of repeated indexes when evaluating the risk of stock exchange market, this paper uses random forest and two-way LSTM model to evaluate and study the risk model of stock exchange market. Firstly, random forest method is used to screen the primary indexes to remove the repetitive indexes in the index system; Secondly, the two-way LSTM model is used to improve the accuracy of various indicators and obtain the evaluation results; Finally, by comparing the evaluation results of random forest with those of two-way LSTM model and other model experimental methods, it is found that random forest plus two-way LSTM model can improve the investment income of investors more accurately.

Copyright

© 2023 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  - Yunlan Xue
AU  - Jian Yao
PY  - 2023
DA  - 2023/08/10
TI  - Evaluation of Stock Market Risk Model Based on Random Forest + Two-Way LSTM
BT  - Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
PB  - Atlantis Press
SP  - 912
EP  - 922
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-198-2_95
DO  - 10.2991/978-94-6463-198-2_95
ID  - Xue2023
ER  -