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Towards Automated Event Studies Using High Frequency News and Trading Data

机译：使用高频新闻和交易数据进行自动化事件研究

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摘要

Event studies have a long history in academic research and were used in disciplines as diverse as economics, law, information technology, marketing, and finance. One of the main challenges is that the process of undertaking such an event study is complex and many assumptions, trade-offs and design decisions need to be made. Based on Service-Oriented Computing principles, this paper proposes a business process on how to undertake and partly automate complex event studies on effects of (un)scheduled news on stocks prices using high frequency trading and news data. The proposed business process is illustrated using a case study that shows how to identify effects of unscheduled news on stock prices in the German DAX30 index.
机译：事件研究在学术研究中具有悠久的历史，并被广泛用于经济学，法律，信息技术，市场营销和金融等学科。主要挑战之一是进行此类事件研究的过程很复杂，需要做出许多假设，权衡取舍和设计决策。基于面向服务的计算原理，本文提出了一种业务流程，该流程涉及如何使用高频交易和新闻数据对（非）计划新闻对股票价格的影响进行复杂的事件研究并使其部分自动化。通过案例研究说明了拟议的业务流程，该案例研究显示了如何在德国DAX30指数中识别计划外新闻对股票价格的影响。

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