We develop FinBERT, a state-of-the-art large language model that adapts to the finance domain. We show that FinBERT incorporates finance knowledge and can better summarize contextual information in financial texts. Using a sample of researcher-labeled sentences from analyst reports, we document that FinBERT substantially outperforms the Loughran and McDonald ... Read More

Financial technology is transforming the world of financial services. Using big data analytics to enhance decision-making in areas such as portfolio and risk management has become a top priority for many financial institutions. Thanks to HKUST’s Yi Yang and co-researchers, institutions and investors now have a novel system for predicting financial risk that ... Read More

Massive amounts of unstructured textual data, such as large volumes of online consumer reviews, “provide an unprecedented opportunity for firms to understand consumer word-of-mouth, forecast product sales, and monitor product defects,” say HKUST’s Yi Yang and a colleague. Topic modeling is a popular textual analysis technique to analyze such data. However ... Read More

With the increasing digitization of economic and social transactions and the rapid growth of user-generated data, unprecedentedly large amounts of textual data are being generated, such as customer reviews on e-commerce platforms and discussions in online communities. However, to obtain real insights from such data, effective computational methods that ... Read More