Research on Stock Index Forecasting Based on Machine Learning

DOI

10.2991/icmmct-18.2018.12How to use a DOI?

Keywords

Stock index, Machine learning, Support vector machine

Abstract

Stock price index prediction is an important part of stock investment. Due to the highly nonlinear and highly noisy features of the volatility of stock market, it is extremely difficult to predict stock price trend. In this paper, we use machine learning method to give stock price index prediction model based on support vector machine. The whole prediction process of stock index forecasting based on machine learning includes the steps of data acquisition, data pre-process, eigenvector solution and normalization treatment. Among them, we should make use of the linear mapping and genetic algorithm to optimize the parameters to improve the Machine Learning method. Practice has proved that this method gives full play to the stability advantage of machine learning and improves the accuracy of prediction.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yanyan Zhuo
PY  - 2018/06
DA  - 2018/06
TI  - Research on Stock Index Forecasting Based on Machine Learning
BT  - Proceedings of the 2018 6th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2018)
PB  - Atlantis Press
SP  - 66
EP  - 72
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-18.2018.12
DO  - 10.2991/icmmct-18.2018.12
ID  - Zhuo2018/06
ER  -