Comparison of SVM and ARIMA Model in Stock Market

DOI

10.2991/978-94-6463-036-7_137How to use a DOI?

Keywords

machine learning; support vector machine (SVM); Autoregressive Integrated Moving Average model (ARIMA); Stock price movement prediction

Abstract

Forecasting the price of one certain asset is always a research hotspot in the financial area. This paper studies which of SVM model and ARIMA model is more suitable for short-term stock forecasting. This paper use SVM model and ARIMA model to predict the stocks of Tesla, Apple, Meta and Amazon, respectively. Next, the paper compares the accuracy of the two models and test which of the two models is suitable for the short-term prediction of the stock market. For the four companies studied in this article, ARIMA model is more accurate than SVM model in short-term stock price prediction. The results in this paper benefit the related investors in financial markets.

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  - Yuxuan Zhu
PY  - 2022
DA  - 2022/12/31
TI  - Comparison of SVM and ARIMA Model in Stock Market
BT  - Proceedings of the 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022)
PB  - Atlantis Press
SP  - 928
EP  - 934
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-036-7_137
DO  - 10.2991/978-94-6463-036-7_137
ID  - Zhu2022
ER  -