International Congress on Eurasian Economies
26-28 June 2024 – Bishkek, KYRGYZSTAN
Paper properties
Paper ID : 2908
Status : Paper published
Language : English
Topic : Finance and Financial Crises
Presenter: Dr. Abdullah Kürşat Merter
Session : 3A Finance
Are Delayed Annual Reports a Sign of Bad News? A Predictive Analysis Using Machine Learning And Sentiment Analysis
Are Delayed Annual Reports a Sign of Bad News? A Predictive Analysis Using Machine Learning And Sentiment Analysis
- Dr. Abdullah Kürşat Merter (Gebze Teknik University, Türkiye)
- Dr. Yavuz Selim Balcıoğlu (Gebze Technical University, Türkiye)
- Research assistant Sedat Çerez (Gebze Teknik University, Türkiye)
- Prof. Dr. Gökhan Özer (Kyrgyz-Turkish Manas University, Kyrgyzstan)
Abstract
This research offers a pioneering investigation into the potential implications of late annual report announcements in the context of BIST100 companies. Annual reports serve as a pivotal source of comprehensive information, enabling stakeholders to evaluate a company's financial health, growth prospects, operational strategies, and potential risks. Recognizing this, our study harnesses artificial intelligence (AI) to scrutinize the timeliness of annual report announcements and their inherent sentiment. Using AI, we constructed a predictive model based on the announcement dates of annual reports between 2009 and 2021. The model estimated the release dates for 2022, facilitating the identification of companies that released their reports later than expected. These delayed reports were then subjected to an in-depth text mining, sentiment analysis, and schema analysis. Our text mining process utilized the robust Hidden Dirichlet Allocation (LDA) Subject Salient Terms (TST) method, known for its efficacy in revealing concealed topics in large text volumes. Our findings were striking; around 87% of statements in the delayed annual reports reflected a negative sentiment, while only 13% displayed a positive tone. Thus, late annual report announcements tend to have a generally pessimistic outlook, indicating they might indeed be bearers of adverse news. This research offers a unique perspective on the relationship between the timeliness of financial reports and the contained sentiment, ultimately contributing to the enhanced transparency and informed decision-making in financial markets. The study underscores the necessity for companies to maintain timely communication and suggests potential areas of interest for future investigations.
JEL codes: M41, C13, C53
Merter, Abdullah Kürşat , Balcıoğlu, Yavuz Selim, Çerez, Sedat , Özer, Gökhan (2024). "Are Delayed Annual Reports a Sign of Bad News? A Predictive Analysis Using Machine Learning And Sentiment Analysis " in Proceedings of International Conference of Eurasian Economies 2024, pp.23-27, Bishkek, KYRGYZSTAN.
DOI: https://doi.org/10.36880/C16.02908
