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

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.

[1]  A. Leone,et al.  Measuring Qualitative Information in Capital Markets Research , 2009 .

[2]  J. Campbell,et al.  Event Studies in Economics and Finance , 1997 .

[3]  Jan Muntermann,et al.  Intraday Stock Price Effects of Ad Hoc Disclosures: The German Case , 2007 .

[4]  P. Asquith.  Merger bids, uncertainty, and stockholder returns☆ , 1983 .

[5]  Robert J. Kauffman,et al.  Research Commentary - Information Transparency in Business-to-Consumer Markets: Concepts, Framework, and Research Agenda , 2010, Inf. Syst. Res..

[6]  Michael Siering,et al.  Investigating the Impact of Media Sentiment and Investor Attention on Financial Markets , 2012, FinanceCom.

[7]  Chenchuramaiah T. Bathala.  Giving Content to Investor Sentiment: The Role of Media in the Stock Market , 2007 .

[8]  Ronald W. Masulis,et al.  Seasoned Equity Offerings: An Empirical Investigation , 1986 .

[9]  Deborah J. Lucas,et al.  Equity Issues and Stock Price Dynamics , 1989 .

[10]  David B. Dunson,et al.  Probabilistic topic models , 2011, KDD '11 Tutorials.

[11]  D. Larcker,et al.  Detecting Deceptive Discussions in Conference Calls , 2012 .

[12]  Andreas Neuhierl,et al.  Market Reaction to Corporate Press Releases , 2010, Journal of Financial and Quantitative Analysis.

[13]  S. Kothari,et al.  The Effect of Disclosures by Management, Analysts, and Business Press on Cost of Capital, Return Volatility, and Analyst Forecasts: A Study Using Content Analysis , 2009 .

[14]  Daniel E. O'Leary,et al.  Event Study Methodologies in Information Systems Research , 2011, Int. J. Account. Inf. Syst..

[15]  Dirk Neumann,et al.  Information Processing in Electronic Markets: Measuring Subjective Interpretation Using Sentiment Analysis , 2012, ICIS.

[16]  William S. Krasker,et al.  Stock Price Movements in Response to Stock Issues under Asymmetric Information , 1986 .

[17]  J. Poterba,et al.  What moves stock prices? , 1988 .

[18]  E. Henry.  Are Investors Influenced By How Earnings Press Releases Are Written? , 2006 .

[19]  M. Narasimha Murty,et al.  On Finding the Natural Number of Topics with Latent Dirichlet Allocation: Some Observations , 2010, PAKDD.

[20]  Marianne Bradford,et al.  Information technology outsourcing and organizational restructuring: An explanation of their effects on firm value , 2005 .

[21]  Shivaram Rajgopal,et al.  The Economic Implications of Corporate Financial Reporting , 2005 .

[22]  Michael McGill,et al.  Introduction to Modern Information Retrieval , 1983 .

[23]  P. Asquith,et al.  Equity issues and offering dilution , 1986 .

[24]  Stefan Feuerriegel,et al.  Generating Domain-Specific Dictionaries using Bayesian Learning , 2015, ECIS.

[25]  E. Fama.  EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* , 1970 .

[26]  Stefan Feuerriegel,et al.  Enhancing Sentiment Analysis of Financial News by Detecting Negation Scopes , 2015, 2015 48th Hawaii International Conference on System Sciences.

[27]  Kurt Hornik,et al.  topicmodels : An R Package for Fitting Topic Models , 2016 .

[28]  Robert J. Kauffman,et al.  Information transparency in business-to-consumer markets , 2010 .

[29]  Dirk Neumann,et al.  Automated news reading: Stock price prediction based on financial news using context-capturing features , 2013, Decis. Support Syst..

[30]  James Allan,et al.  A Comparative Study of Utilizing Topic Models for Information Retrieval , 2009, ECIR.

[31]  Peter R. Dodd,et al.  Merger proposals, management discretion and stockholder wealth , 1980 .

[32]  Tim Loughran,et al.  When is a Liability not a Liability? Textual Analysis, Dictionaries, and 10-Ks , 2010 .

[33]  Dirk Neumann,et al.  Reading All the News at the Same Time: Predicting Mid-term Stock Price Developments Based on News Momentum , 2013, 2013 46th Hawaii International Conference on System Sciences.

[34]  Stefan Feuerriegel,et al.  News or Noise? How News Drives Commodity Prices , 2013, ICIS.

[35]  Thomas L. Griffiths,et al.  A probabilistic approach to semantic representation , 2019, Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society.

[36]  Stefan Feuerriegel,et al.  Detecting Negation Scopes for Financial News Sentiment Using Reinforcement Learning , 2016, 2016 49th Hawaii International Conference on System Sciences (HICSS).

[37]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..