An Analysis of Optimistic and Pessimistic Language in Earnings Press Releases

Exposé Écrit pour un Séminaire / Cours , 2011 , 17 Pages

Informatique - Informatique Appliquée à la Gestion

Earnings press releases are the major news event of the season for companies and investors, analysts, financial media and the market. As framework of investor relations (IR) they communicate the financial performance in numerical and narrative forms. For example, earnings press releases are obligatory for firms listed on the New York Stock Exchange (NYSE).
There are several rules and guidelines how to prepare them. An accurate earnings press release contains, apart from analyses of operating results, historical data, positive and negative factors affecting key financial indicators, a realistic and truthful forecast of future quarters.
Whereas numerous studies focus on interpretation of numerical forms in earnings press releases, this paper examines the influence of optimistic and pessimistic language in earnings press releases on future firm performance with several studies. It also opposes different approaches to measure the tone.
Based on the study “Beyond the Numbers: An Analysis of Optimistic and Pessimistic Language in Earnings Press Releases” published by Davis, Piger and Sedor the paper presents a textual analysis approach with DICTION 5.0. The authors have been the first scientists so far to examine the role language plays in the credible communication of information to investors.
The dictionary-based content analysis program DICTION 5.0 is able to identify subtle aspects of language. The systematic textual analysis techniques are based on pre-existing search rules. It is able to analyze a larger sample size than possible by human coding or manual reading.
Apart from this, statistical methods – like the naïve Bayesian learning algorithm, reducing a given sentence to a list of words – are introduced and compared with each other.
Given the different approaches to analyze the impact of language in earnings press releases to future earnings a positive correlation between optimistic language and future firm performance can be stated.
Bearing in mind that earnings press releases may use a promotional presentation style of company’s development and opportunistic behavior to delude investors is feasible, current and future applications should be discussed critically.

Inhaltsverzeichnis (Table of Contents)

• 1. INTRODUCTION
• 2. EARNINGS PRESS RELEASES
• 3. TEXTUAL ANALYSIS OF OPTIMISTIC AND PESSIMISTIC LANGUAGE
  • 3.1 Data Sample
  • 3.2 Dictionary approach with DICTION 5.0
  • 3.3 Descriptive Evidence
  • 3.4 Correlation between language usage and future firm performance
  • 3.5 Market response to optimistic and pessimistic language
• 4. A DIFFERENT APPROACH: NAÏVE BAYESIAN LEARNING ALGORITHM
• 5. SIMILAR STUDIES
• 6. EXCURSUS: A PROSPECTIVE BUSINESS RATIO
  • 6.1 The Business Ratio
  • 6.2 The Data sample
  • 6.3 The Application of NETOPT ratio
  • 6.4 Flaws of NETOPT ratio
• 7. CONCLUSIONS
• APPENDIX: DECLARATION OF THE ACCOUNTING AND FINANCIAL VARIABLES
• REFERENCES AND READING LIST

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This seminar paper examines the influence of optimistic and pessimistic language in earnings press releases on future firm performance. It compares different approaches to measure the tone of these releases, focusing on the dictionary-based content analysis program DICTION 5.0 and the naïve Bayesian learning algorithm. The paper also explores the market response to optimistic and pessimistic language and investigates the potential application of these findings to create a business ratio.

• The impact of optimistic and pessimistic language on future firm performance
• Comparison of different approaches to measure tone in earnings press releases
• Market response to optimistic and pessimistic language
• Development of a business ratio based on language analysis
• Analysis of the role of language in credible communication of information to investors

Zusammenfassung der Kapitel (Chapter Summaries)

Chapter 1 introduces the topic of earnings press releases and their importance in communicating firm performance to investors. It highlights the focus of the paper on the influence of optimistic and pessimistic language on future firm performance and outlines the different approaches to measuring tone that will be explored. Chapter 2 delves into the rules and best practices for publishing earnings press releases, emphasizing the importance of accurate and truthful communication while avoiding misleading statements. It also discusses the challenges of analyzing narrative form in disclosures compared to numerical data.

Chapter 3 presents the textual analysis approach using DICTION 5.0, focusing on the study by Davis et al. (2006). It describes the data sample, the dictionary-based content analysis program, and the results of the analysis, including the correlation between language usage and future firm performance. Chapter 4 introduces an alternative approach using the naïve Bayesian learning algorithm, comparing its advantages and drawbacks to the dictionary-based approach.

Chapter 6 explores a potential application of the findings by developing a business ratio based on the connection between language and future firm performance. Finally, Chapter 7 concludes the paper, summarizing the key findings and discussing the implications of the research.

Schlüsselwörter (Keywords)

The keywords and focus themes of the text include earnings press releases, optimistic and pessimistic language, textual analysis, DICTION 5.0, naïve Bayesian learning algorithm, firm performance, market response, business ratio, investor relations, and credible communication.

• Université: University of Freiburg (Chair of Information Systems Research)
• Auteur: cand. rer. pol. Marius Rombach (Auteur)
• Année de publication: 2011
• Pages: 17
• N° de catalogue: V180864
• ISBN (ebook): 9783656039280
• ISBN (Livre): 9783656040446
• Langue: anglais
• mots-clé: Optimistic Language, tone, Earnings Press Releases, Pessimistic Language, DICTION, textual analysis, Bayesian, future firm performance, financial performance, Information Content, Financial Markets