Testing the Market Efficiency by LSTM and SVM

DOI

10.2991/978-94-6463-036-7_86How to use a DOI?

Keywords

stock index prediction; SVM; LSTM; market efficiency

Abstract

As an essential part of risk investment and a microcosm of the national economy, predicting the stock market’s change accurately and efficiently becomes extremely important. The purpose of this paper is to evaluate the accuracy of SVM and LSTM models to judge whether the Efficient Markets Hypothesis (EMH) is correct or not by predicting the typical stock indexes of the relatively mature American stock market and the gradually mature Chinese stock market. Therefore, this article applies the Kaggle Data Set to predict the stock price of S&P 500 and SSEC from January 01, 2013 to January 01, 2018 by using both the LSTM model and the SVM model. First, this paper compares the predicted trends with the actual trend respectively. Second, this paper compares the two stocks and concludes the efficiency of markets in different countries. Third, this paper analyzes the influence of different policies on stock market fluctuation to explain the unpredictable change in the stock market. Finally, according to the results, the statistically significant conclusions are drawn that LSTM is more stable and accurate than SVM in the stock indexes prediction and American stock market is more effective than the Chinese stock market. Therefore, relevant forecasters can be more inclined to use LSTM model when making predictions.

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  - Tengyue Zhang
PY  - 2022
DA  - 2022/12/31
TI  - Testing the Market Efficiency by LSTM and SVM
BT  - Proceedings of the 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022)
PB  - Atlantis Press
SP  - 584
EP  - 590
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-036-7_86
DO  - 10.2991/978-94-6463-036-7_86
ID  - Zhang2022
ER  -