Using Negations in Analyzing German Texts in Finance - Matthias Pöferlein (Credit and Capital Markets – Kredit und Kapital, 2023)
Domain-specific dictionaries have prevailed, when conducting the dictionary-based approach to measure the sentiment of textual data in finance. Through the contributions of Bannier et al. (2019a) and Pöferlein (2021), two versions of a dictionary suitable for analyzing German finance-related texts are available (BPW dictionary). This paper conducts and tests further improvements of the given word lists by calculating the sentiment of German-speaking annual reports to forecast future return on assets and future return on equity. This corrected and expanded version provides more significant results. Despite the broad usage of negations, this type of improvement in combination with the BPW dictionary has not yet been tested when conducting the dictionary-based approach. Therefore, this paper additionally tests different negation lists to show that implementing negations can improve results.
Keywords: G14; G17; 330; Textual Analysis; Textual Sentiment; Sentiment Analysis; Content Analysis; Negations; Annual Reports