应用文本情感分析和主成分分析解决融资融券风险量化问题

Research on Quantitative Risk of Margin Trading Based on Text Analysis and Principal Component Analysis

摘要: 融资融券制度为我国股市交易注入了新的活力，激发了广大投资者和券商的积极参与。我国监管机构虽然制定了严格的交易制度，但其系统性风险仍不容忽视。因此，本文针对如何量化融资融券业务风险问题进行了建模求解。首先通过Python爬虫和数据库下载的方式获取财务信息、股吧评论、新闻公告等与融资融券风险相关的数据，其中，针对非结构化数据运用了文本情感分析进行模糊信息的挖掘。其次，对所有指标与融资融券风险进行相关性分析，最终选取出13个与融资融券风险相关的指标，运用主成分分析法计算每个指标影响融资融券风险的权重，建立了融资融券风险量化模型。研究结果有助于厘清关键财务指标以及以股吧评论为代表的模糊信息影响融资融券风险的路径和机理，并为有效量化融资融券风险提供了一定的借鉴思路。

Abstract: The margin trading system has injected new vitality into China’s stock market trading and stimu-lated the active participation of investors and securities traders. Although China’s regulatory au-thorities have formulated a strict trading system, its systematic risks cannot be ignored. Therefore, this paper models and solves the problem of how to quantify the risk of margin trading. First, the data related to the risk of margin trading, such as financial information, stock bar comments, news bulletins, etc., are obtained through Python crawlers and database downloads. Among them, text emotion analysis is used to mine fuzzy information for unstructured data. Secondly, the paper ana-lyzes the correlation between all indicators and the risk of margin trading, finally selects 13 indica-tors related to the risk of margin trading, calculates the weight of each indicator affecting the risk of margin trading using the principal component analysis method, and establishes a quantitative model of the risk of margin trading. The research results are helpful to clarify the path and mecha-nism of the impact of key financial indicators and fuzzy information represented by stock bar com-ments on the risk of margin trading, and provide some reference ideas for effectively quantifying the risk of margin trading.