The enhanced classification for the stock index prediction

被引：8

作者：

Kim, Hyeuk ^{[1
]}

Han, Sang Tae ^{[1
]}

机构：

[1] Hoseo Univ, Dept Appl Stat, Asan 31499, Chungcheongnam, South Korea

来源：

PROMOTING BUSINESS ANALYTICS AND QUANTITATIVE MANAGEMENT OF TECHNOLOGY: 4TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT (ITQM 2016) | 2016年 / 91卷

关键词：

Bootstrap; Random forests; Stock price prediction;

D O I：

10.1016/j.procs.2016.07.077

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

It is one of the hardest challenges to predict the movement of the stock price. We propose the modified bootstrap method in random forests to predict the direction of movement of the stock index price. The training set generated by the modified bootstrapping considers the impact of response variable simultaneously and is applied in random forests. The real KOSPI data are used for the experiments and the result shows that the proposed method performs better than the original method in various situations. (C) 2016 Published by Elsevier B.V.

引用

页码：284 / 286

页数：3

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