Evaluation of News-Based Trading Strategies

机译：评估新闻的交易策略

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摘要

The marvel of markets lies in the fact that dispersed information is instantaneously processed by adjusting the price of goods, services and assets. Financial markets are particularly efficient when it comes to processing information; such information is typically embedded in textual news that is then interpreted by investors. Quite recently, researchers have started to automatically determine news sentiment in order to explain stock price movements. Interestingly, this so-called news sentiment works fairly well in explaining stock returns. In this paper, we attempt to design trading strategies that are built on textual news in order to obtain higher profits than benchmark strategies achieve. Essentially, we succeed by showing evidence that a news-based trading strategy indeed outperforms our benchmarks by a 9.06-fold performance.

机译：市场奇迹在于通过调整商品，服务和资产价格来瞬间处理分散信息。在处理信息时，金融市场特别有效;这些信息通常嵌入文本新闻中，然后被投资者解释。最近，研究人员已经开始自动确定新闻情绪以解释股价走势。有趣的是，这种所谓的新闻情绪在解释股票回报方面相当好。在本文中，我们试图设计基于文本新闻的交易策略，以获得比基准策略实现更高的利润。基本上，我们通过显示证据表明，基于新闻的交易策略确实以9.06倍的表现优于我们的基准。

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来源
《International workshop on enterprise applications and services in the finance industry》|2015年||共16页
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作者
Stefan Feuerriegel; Dirk Neumann;
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正文语种
中图分类电子贸易、网上贸易;
关键词
Financial news; Decision support; Trading strategies Text mining; Sentiment analysis;

机译：财经新闻;决策支持;交易策略文本挖掘;情绪分析;

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4. Evaluation of News-Based Trading Strategies [C] . Stefan Feuerriegel, Dirk Neumann International workshop on enterprise applications and services in the finance industry . 2015

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Evaluation of News-Based Trading Strategies

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