Application of Fuzzy C-Means Clustering and Support Vector Machine in Stock Price Analysis

DOI

10.2991/978-94-6463-198-2_83How to use a DOI?

Keywords

Fuzzy Clustering Algorithm; Correlation Index Method; Support vector machine; Stock Price; Price Prediction

Abstract

With the rapid development of the global economy and the continuous expansion of the investment scale in the financial market, more and more transaction data and market public opinion information are generated in the stock market under the background of big data, which makes it more difficult for investors to distinguish effective investment information. This paper presents a stock price prediction method based on fuzzy clustering and support vector machine. Fuzzy clustering has the characteristics of high accuracy when processing large data. When analyzing the financial information of listed companies, fuzzy clustering technology and related index method can effectively reduce the error. Through the analysis of the factors influencing stock value investment, this paper selects five aspects from the financial statements of listed companies that can reflect their profitability, development ability, shareholders’ profitability, solvency and management ability. This paper pays attention to the verification of the theoretical method model, using fuzzy clustering, support vector machine and bp neural network to compare the data, to ensure the effectiveness of its practical application. In this paper, the real data of China’s stock market are used for testing. The accuracy and recall rate of mohujulei model are relatively stable, with the accuracy of 0.884 and 0.001 respectively. The research of this paper is helpful to improve the quantity and quality of listed companies.

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  - Jinliang Wang
AU  - Wennan Wang
AU  - Tuli Chen
AU  - Fu Luo
AU  - Shiyang Song
PY  - 2023
DA  - 2023/08/10
TI  - Application of Fuzzy C-Means Clustering and Support Vector Machine in Stock Price Analysis
BT  - Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
PB  - Atlantis Press
SP  - 800
EP  - 807
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-198-2_83
DO  - 10.2991/978-94-6463-198-2_83
ID  - Wang2023
ER  -