基于金融文本的市场行情预测方法研究Research on Methodology of Market Trends Prediction

Based on Financial Text

2018年5月16日

汇报人：王玮玮

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1 实验室研究架构（AI通用工程平台）

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1 实验室研究架构（AI通用工程平台）

1.1 研究概览

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1 实验室研究架构（AI通用工程平台）

1.2 研究场景图

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2 Motivation

Financial news text, known as one major source of market information, are widely used and analyzed by investors.

Our research mainly focuses on forecasting market trends based on financial news text. We try to answer several challenging questions: (1) How to extract financial web main content automatically? (2) How to mining text feature and build model to predict market trends?

We have developed an internet financial news crawler and propose a machine learning method to to extract news content automatically. We further apply financial news text for analyzing market trends using SVM, LR and XGBoost.

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3 Crawl (Finish)

https://git.xmu.edu.cn/FinancialTextMining/ScrapySpiderhttps://git.xmu.edu.cn/FinancialTextMining/SpiderMoniterhttps://git.xmu.edu.cn/FinancialTextMining/SpiderKeeper

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4 Content Extraction from Financial News Using XGBoost

• 数据：爬取的金融新闻网页• 打标签：按DOM树的最小粒度划分，对每个tag打标签，main

content => 1, noise text => 0• 特征抽取：Text Length、Tag Path、CSS Properties等• 模型选择：XGBoost• 评价指标：准确率、召回率、F1 score

• 创新点：1. 针对金融新闻网页的正文自动化抽取2. 使用XGBoost模型

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5 STOCK PRICE MOVEMENTS PREDICTION with TEXTUAL INFORMATION（待发表）

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Thanks