Analysis of How Underlying Topics in Financial News Affect Stock Prices Using Latent Dirichlet Allocation

Abstract

Companies listed on the stock markets are typically obliged to publicly disclose any information that might have a significant influence on their stock prices. This transparency regulation is intended to ensure that all market participants have access to the same information. The corresponding press releases are one of the most reliable news sources concerning a company's operations. Interestingly, even though researcher have investigated the timing of releases, research has invested little effort into examining the underlying news topics. In this paper, we analyze the effects of topics found in such corporate press releases on stock market returns in the German market. We determine the topic of ad hoc announcements by using Latent Dirichlet Allocation. Effectively, we succeed in extracting 40 topics. As hypothesized, the effect of these topic groups differ greatly from each other. Some topics have no resulting effect on abnormal returns of stocks, whereas other topics, such as drug testing, exhibit a large effect.

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