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摘要翻译：
沟通现在是央行货币政策工具包中的标准工具。理论上，沟通为中央银行提供了引导公众预期的机会，实证表明中央银行沟通会导致金融市场波动。然而，很少有人研究信息的哪些维度或主题在引起这些波动中最重要。我们开发了一种半自动的方法，它将FOMC的声明总结为其主要主题，基于一致性自动选择最佳模型，并使用机器学习文献中的主题建模方法评估这些主题是否对美国国债收益率曲线的形状有重大影响。我们的研究结果表明，联邦公开市场委员会的声明可以分解为三个主题：（一）与经济状况和任务有关的信息；（二）与货币政策工具和中间目标有关的信息；（三）与金融市场和金融危机有关的信息。我们发现，在金融危机期间，报表的影响最大，并且通过与金融主题相关的信息，报表的影响主要表现在收益率曲线的曲率上。
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英文标题：
《Central Bank Communication and the Yield Curve: A Semi-Automatic
Approach using Non-Negative Matrix Factorization》
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作者：
Ancil Crayton
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最新提交年份：
2018
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分类信息：
一级分类：Economics 经济学
二级分类：General Economics 一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Computer Science 计算机科学
二级分类：Computation and Language 计算与语言
分类描述：Covers natural language processing. Roughly includes material in ACM Subject Class I.2.7. Note that work on artificial languages (programming languages, logics, formal systems) that does not explicitly address natural-language issues broadly construed (natural-language processing, computational linguistics, speech, text retrieval, etc.) is not appropriate for this area.
涵盖自然语言处理。大致包括ACM科目I.2.7类的材料。请注意，人工语言（编程语言、逻辑学、形式系统）的工作，如果没有明确地解决广义的自然语言问题（自然语言处理、计算语言学、语音、文本检索等），就不适合这个领域。
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一级分类：Quantitative Finance 数量金融学
二级分类：Economics 经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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英文摘要：
Communication is now a standard tool in the central bank's monetary policy toolkit. Theoretically, communication provides the central bank an opportunity to guide public expectations, and it has been shown empirically that central bank communication can lead to financial market fluctuations. However, there has been little research into which dimensions or topics of information are most important in causing these fluctuations. We develop a semi-automatic methodology that summarizes the FOMC statements into its main themes, automatically selects the best model based on coherency, and assesses whether there is a significant impact of these themes on the shape of the U.S Treasury yield curve using topic modeling methods from the machine learning literature. Our findings suggest that the FOMC statements can be decomposed into three topics: (i) information related to the economic conditions and the mandates, (ii) information related to monetary policy tools and intermediate targets, and (iii) information related to financial markets and the financial crisis. We find that statements are most influential during the financial crisis and the effects are mostly present in the curvature of the yield curve through information related to the financial theme.
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PDF链接：
https://arxiv.org/pdf/1809.08718
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