Financial Report Sentiment Analysis Using Loughran-mcdonald Dictionary and BERT

Abstract

In the ever-changing world of financial markets, understanding investor behavior and making informed decisions relies heavily on sentiment analysis. This study delves into the integration of traditional techniques, such as the Loughran- McDonald dictionary, with advanced natural language processing (NLP) methods utilizing BERT (Bidirectional Encoder Representations from Transformers). The goal is to enhance the accuracy and depth of sentiment analysis in financial reports.To begin, we employ the specialized Loughran-McDonald dictionary designed for financial sentiment analysis. This lexicon includes domainspecific word lists for positive and negative sentiments, forming a solid foundation for sentiment scoring. Expanding on this foundation, we incorporate BERT, an advanced transformerbased NLP model. BERT’s contextual understanding of language and ability to capture intricate semantic relationships within financial texts aim to overcome the limitations of rule-based sentiment analysis. The methodology involves preprocessing financial reports, integrating Loughran-McDonald sentiment scores, and fine-tuning BERT for financial sentiment classification. This hybrid approach leverages both the domain expertise encoded in the dictionary and BERT’s contextual comprehension of financial jargon and nuances. We validate and evaluate our implementation using a diverse dataset comprising quarterly earnings releases, annual reports, and other relevant disclosures. Performance metrics such as precision, recall, and F1 score are analyzed to assess the effectiveness of our hybrid approach compared to individual methods. The findings have significant implications for financial analysts, investors, and policymakers by providing a more nuanced understanding of sentiment in financial reports. Our hybrid approach aims to offer improved accuracy in capturing sentiment polarity while facilitating more informed decision-making in today’s complex and dynamic realm of financial markets.