Learn about the transformative potential, challenges, and cutting-edge technologies associated with harnessing data from social media and news platforms for financial market surveillance.

Learn about the groundbreaking Stellaris GPT, a large language model developed in Hong Kong with hundreds of billions of parameters. 

This webinar showcases the importance of data visualization in relaying analytics results and crafting compelling data-driven stories, showcasing successful and cautionary examples to illustrate effective practices.

In this webinar, Dr. Chao He demonstrates the game-changing potential of artificial intelligence and natural language processing (NLP) in empowering financial institutions to proactively identify and mitigate risks, make informed decisions, and seize opportunities ahead of the curve.

This research examines sentiment contagion in social media, revealing its influence and providing valuable insights into how exposure content and individual heterogeneity impact the contagious spread of sentiments.

In this webinar, the speaker will provide an overview of predictive analytics, including its benefits, use cases, and best practices.

In this talk, the speaker will introduce FinBERT, a state-of-the-art large language model that adapts to the finance domain.

This session will provide an overview of the sustainability regulatory strategy and how it is shaping the sustainability financial ecosystem.

This webinar will shed light on the sustainable finance markets, which have expanded rapidly over the past decade from a fringe “movement” to sizeable markets providing significant financing and investing opportunities.

This webinar will provide a contemporary view of the ESG disclosure landscape, covering current best practices across regions including Europe, Mainland China, and Hong Kong.

This research suggests that introducing monetary incentives can be a viable business model for knowledge platforms to stimulate user contributions in both paid and related unpaid activities.

This webinar will provide an overview of a large-scale social media analysis of COVID-19 in Hong Kong, including the development of a Cantonese sentiment classification model to gauge public approval of anti-epidemic policies and the proposal of a keyphrase extraction technique to further extract public opinions.

This webinar will provide an overview of a pre-trained financial domain-specific BERT model, FinBERT, that uses a large corpus of financial communication. The work empirically shows that FinBERT outperforms simpler NLP tasks and the generic domain BERT model. 

In this webinar, the speaker will discuss the effect of different choice capacities on the number of choices and matches made on a platform by conducting a randomized field experiment in collaboration with an online dating platform.