A Survey of Neural Network Techniques in Market Trend Analysis

被引：0
|
作者：
Katarya, Rahul [1 ]
Mahajan, Anmol [1 ]
机构：
[1] Delhi Technol Univ, Dept Informat Technol, Bawana Rd, Delhi 42, India
来源：
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT SUSTAINABLE SYSTEMS (ICISS 2017) | 2017年
关键词：
Neural Networks; Deep Learning; Trend Analysis; Financial Time Series; Machine Learning;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a survey on the efficacy of neural network models in predicting market trends is performed by presenting a detailed taxonomy of a few recently proposed models. After surveying the results presented, it is demonstrated that neural networks can be superior when applied to trading simulation, and have greater potential to model noisy financial data compared to traditional classifier approaches.
引用
收藏
页码：873 / 877
页数：5
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