DeepEye：一个基于深度学习的程序化交易识别与分类方法

徐广斌; 张伟

doi:10.11959/j.issn.2096-0271.2018053

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DeepEye：一个基于深度学习的程序化交易识别与分类方法

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- DeepEye：一个基于深度学习的程序化交易识别与分类方法
- DeepEye:a deep learning-based method of recognition and classification of program trading
- 大数据 2018年4卷第5期页码：2018053
- 作者机构：
  
  1. 上海证券交易所资本市场研究所，上海 200120
  2. 上海证券交易所产品创新中心，上海 200120
- 作者简介：
  
  [ "徐广斌（1976-），男，博士，上海证券交易所资本市场研究所高级工程师、业务主管，主要研究方向为证券信息技术、大数据、金融计算。" ]
  [ "张伟（1989-），男，就职于上海证券交易所产品创新中心，主要研究方向为金融工程。" ]
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2018053
  中图分类号： TP393
- 网络首发：2018-09，
  
  纸质出版：2018-09-15
- 稿件说明：
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徐广斌, 张伟. DeepEye：一个基于深度学习的程序化交易识别与分类方法[J]. 大数据, 2018,4(5):2018053.

Guangbin XU, Wei ZHANG. DeepEye:a deep learning-based method of recognition and classification of program trading[J]. Big Data Research, 2018, 4(5): 2018053.
徐广斌, 张伟. DeepEye：一个基于深度学习的程序化交易识别与分类方法[J]. 大数据, 2018,4(5):2018053. DOI： 10.11959/j.issn.2096-0271.2018053.

Guangbin XU, Wei ZHANG. DeepEye:a deep learning-based method of recognition and classification of program trading[J]. Big Data Research, 2018, 4(5): 2018053. DOI： 10.11959/j.issn.2096-0271.2018053.

摘要

基于沪市A股交易数据，对A股市场程序化交易行为进行系统分析，构建程序化交易识别及分类特征指标体系，结合深度学习技术提出A股市场程序化交易的智能识别与分类方法——DeepEye，该方法可对程序化交易进行识别并分类。在真实交易行为数据集上的实验表明，所提出的方法在识别和分类上取得了较高的准确率，验证了将深度学习用于证券市场行为监管的可行性和有效性。该方法已辅助用于资本市场投资者画像及市场一线行为监管。

Abstract

Program trading behavior in A-share market has been systematically analyzed based on the Shanghai Stock Exchange’s latest trading data and a feature indictor system has thus been built up for characterizing and classifying the program trading in the market.Furthermore

based on the deep learning technology

the A-share program trading intelligentized recognition and classification method

DeepEye

has been proposed

which enables program trading behavior in the market to be recognized and classified.The accuracy of the pilot implementation got about 70% which verified the feasibility and effectiveness of the new method.The proposed method can serve as an auxiliary measure to existing investor portraits and behavior supervision analysis for market regulation and can be a reference for improving the existing program trading regulatory rules.

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references

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