外汇预测:使用新闻文章进行货币趋势建模

Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining Pub Date : 2013-08-11 DOI:10.1145/2487575.2487710

Fang Jin, Nathan Self, Parang Saraf, P. Butler, W. Wang, Naren Ramakrishnan

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引用次数: 41

摘要

金融市场对意料之外的新闻和事件相当敏感。确定新闻对市场的影响是一项具有挑战性的任务。在这个演示中，我们展示了Forex-foreteller (FF)，它可以挖掘新闻文章并预测外汇市场的走势。该系统结合使用语言模型、主题聚类和情感分析来识别相关的新闻文章。这些文章与历史股票指数和货币兑换价值一起用于线性回归模型进行预测。该系统具有专门为触摸敏感设备设计的交互式可视化工具，它可以描述预测以及用于进行预测的按时间顺序排列的新闻事件和财务数据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Forex-foreteller: currency trend modeling using news articles

Financial markets are quite sensitive to unanticipated news and events. Identifying the effect of news on the market is a challenging task. In this demo, we present Forex-foreteller (FF) which mines news articles and makes forecasts about the movement of foreign currency markets. The system uses a combination of language models, topic clustering, and sentiment analysis to identify relevant news articles. These articles along with the historical stock index and currency exchange values are used in a linear regression model to make forecasts. The system has an interactive visualizer designed specifically for touch-sensitive devices which depicts forecasts along with the chronological news events and financial data used for making the forecasts.

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Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining

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