This study is dedicated to the adaptation of the DistilBERT architecture to better interpret the sentiment embedded within monetary policy speeches. While the DistilBERT model has demonstrated its efficacy across various domains, the unique lexicon and subtleties present in central banking communications necessitate specialized tuning. This study involved the meticulous annotation of speech, report, and press release data from the European Central Bank (ECB) and subsequent model fine-tuning. Results underscore the model’s adeptness at discerning sentiment in this specialized context, offering a valuable tool for researchers and analysts examining the intersection of sentiment and monetary policy.
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