大数据与股票市场非规范行为规制:一个分析框架

发布时间：2018-03-29 17:04

本文选题：大数据分析　切入点：数据挖掘　出处：《南方金融》2017年11期

【摘要】：非规范行为是股票市场风险的重要来源,但其较强的隐蔽性增加了识别和防范的难度。为此,有必要运用大数据技术,对股票交易的数量、时间和价格三个变量及其组合进行精准分析,找到引起异常交易的源头并进行预警,提高非规范行为的识别概率;同时对行为主体的证券账户和银行账户信息进行分析,对手机号码、虚拟账户、IP地址等信息进行数据挖掘,形成交叉验证,对非规范行为进行追踪。从事非规范行为的市场主体通常会隐蔽自己的行为和身份,可运用大数据技术进行行为分析和交易复盘,进而为市场主体"画像"。推广运用大数据技术以规制股票市场非规范行为,需要在解决"信息孤岛"问题的基础上,强化信息监管、舆情监测和不同部门之间的监管协同。
[Abstract]:Non-standard behavior is an important source of stock market risk, but its strong concealment makes it more difficult to identify and prevent. Therefore, it is necessary to use big data technology to deal with the quantity of stock trading. Time and price of three variables and their combination of accurate analysis to find the source of abnormal transactions and early warning, improve the identification of non-standard behavior probability; at the same time, the behavior of the main securities account and bank account information analysis, For mobile phone number, virtual account, IP address and other information mining, the formation of cross-validation, non-standard behavior tracking. The non-standard behavior of the market participants will usually conceal their own behavior and identity. Big data technique can be used to conduct behavior analysis and trade review, and then to "portrait" the market subject. In order to promote the use of big data technology to regulate the non-standard behavior of the stock market, it is necessary to solve the problem of "information isolated island". Strengthen information supervision, public opinion monitoring and coordination between different departments.
【作者单位】：广东省农村信用社联合社;
【基金】：广东金融学会2017-2018年度重大决策咨询研究课题《商业银行互联网金融创新研究》(项目编号:GDJRXH201611)的资助
【分类号】：F832.51;TP311.13

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