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Aspect-based sentiment analysis of financial texts for predicting corporate financial performance

Provider: Grantová agentura ČR
Programme: Standardní projekty
Implementation period: 01.01.22 - 31.12.24
Workplace: Fakulta ekonomicko-správní - Centrum pro vědu a výzkum
Investigator: Hájek Petr
Team member: Munk Michal | Myšková Renáta | Kovárník Jaroslav | Boďa Martin
Description:
Sentiment analysis is attracting considerable interest in finance due to its capacity to provide additional insight into opinions and intentions of investors, managers and other stakeholders. A remarkable improvement in predicting corporate financial performance has been achieved when considering the textual sentiment. Previous approaches in this regard have been limited to document-level sentiment analysis of financial texts. However, a more fine-grained aspect-based sentiment analysis is presumably incrementally informative in predicting corporate financial performance because opinions expressed on different aspects of companies can be extracted. Here, we propose to investigate how aspect-based sentiment analysis of firm-related financial texts might predict corporate financial performance. To do this, we combine corporation-expressed, media-expressed, and internet-expressed aspect-based sentiments with quantitative financial information obtained from financial statements and financial markets.