Research on Risk Identification System Based on Random Forest Algorithm-High-Order Moment Model

被引：3
|
作者：
Liu, Li-Jun [1 ]
Shen, Wei-Kang [1 ]
Zhu, Jia-Ming [2 ]
机构：
[1] Hebei GEO Univ, Sch Econ, Shijiazhuang 050031, Hebei, Peoples R China
[2] Anhui Univ Finance & Econ, Inst Quantitat Econ, Bengbu 233030, Peoples R China
来源：
COMPLEXITY | 2021年 / 2021卷
关键词：
Decision trees;
D O I：
10.1155/2021/5588018
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
With the continuous development of the stock market, designing a reasonable risk identification tool will help to solve the irrational problem of investors. This paper first selects the stocks with the most valuable investment value in the future through the random forest algorithm in the nine-factor model and then analyzes them by using the higher-order moment model to find that different investors' preferences will make the weight of the portfolio change accordingly, which will eventually make the optimal return and risk set of the composition of the portfolio change. The risk identification system designed in this paper can provide an effective risk identification tool for investors and help them make rational judgments.
引用
收藏
页数：10
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