摘要翻译：
在接下来的文章中，我们使用主题建模算法和情绪评分方法来构造一个新的度量指标，作为衰退预测模型的领先指标。我们假设，纳入这样一个纯粹来自非结构化新闻数据的情绪指标，将提高我们预测未来衰退的能力，因为它提供了一个直接衡量消费者和生产者所接触到的信息极性的指标。我们继续表明，我们提出的新闻情绪指标，与传统情绪数据，如密歇根消费者情绪指数和采购经理人指数，以及从一个大的经济和金融指标面板中得出的共同因素，有助于显著改善模型的性能。
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英文标题：
《News Sentiment as Leading Indicators for Recessions》
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作者：
Melody Y. Huang, Randall R. Rojas, Patrick D. Convery
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最新提交年份：
2018
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分类信息：

一级分类：Statistics        统计学
二级分类：Applications        应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
  In the following paper, we use a topic modeling algorithm and sentiment scoring methods to construct a novel metric that serves as a leading indicator in recession prediction models. We hypothesize that the inclusion of such a sentiment indicator, derived purely from unstructured news data, will improve our capabilities to forecast future recessions because it provides a direct measure of the polarity of the information consumers and producers are exposed to. We go on to show that the inclusion of our proposed news sentiment indicator, with traditional sentiment data, such as the Michigan Index of Consumer Sentiment and the Purchasing Manager's Index, and common factors derived from a large panel of economic and financial indicators helps improve model performance significantly.
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PDF链接：
https://arxiv.org/pdf/1805.04160