2023 Research Conference
Call For Papers And Participants
ABFER, HKUST, and SUSTech Research Conference on Capital Market Research in the Era of AI
November 3-4, 2023
We are excited to announce a series of research conferences, co-organized by the Asian Bureau of Finance and Economic Research (ABFER), the Hong Kong University of Science and Technology (HKUST), and the Southern University of Science and Technology (SUSTech), on AI applications and the impacts of AI adoption on the economy and society. The inaugural 2023 conference focuses on AI applications in finance and related industries.
This two-day event will bring together academics, industry experts, and regulators in to explore the latest developments, opportunities, and challenges related to investing in the era of AI, particularly in Asia but not limited to just Asia. The conference will take place on November 3-4, 2023, at the HKUST Business School (and the second of the series will take place on Nov 1 and 2, 2024 at SUSTech Business School). The conference is open to anyone interested in learning about the evolving and progressing intersection of AI and investment.
This conference will provide a unique opportunity for attendees to network with like-minded academics and professionals and gain valuable knowledge and insights to help make informed investment decisions. The conference will feature a keynote speech, interactive workshops, and panel discussions on a range of topics related to AI and investment. We invite the submission of research papers in all areas related to the intersection of AI and investment, including but not limited to the following topics. We particularly welcome Asia-related research papers.
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The applications of AI, machine learning, natural language processing, and other novel analytic methods in research for all areas of financial economics.
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The use of unstructured data (e.g., text, images, voice and facial recognition, mobile footprint, satellite data, geolocation, and social media) in investment and related areas such as auditing and assurance.
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Machine learning/AI/high-performance computing in the finance industry and in academic research (e.g., new measures of technological change and innovation, causal inference or structural estimation, technologies for preventing data mining and p-hacking, AI-assisted trading.).
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The social and economic impact of AI adoption, i.e., the opportunities and challenges associated with the widespread adoption of AI and its impact on stakeholders of adopting firms and industries (e.g., supply chain partners, employees, investors etc.)
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The ethical considerations of AI in finance, including issues related to bias and transparency.
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Quantitative investment strategies and portfolio optimization with machine learning technologies or other AI models.
Organizers
Asian Bureau of Finance and Economic Research (ABFER)
Center for Securities Analysis with Financial Technology, The Hong Kong University of Science and Technology (HKUST)
Business School, Southern University of Science and Technology (SUSTech)
Conference Program Committee
Henry Cao, Cheung Kong Graduate School of Business (CKGSB)
Yi Huang, Fudan University
Allen Huang, The Hong Kong University of Science and Technology (HKUST)
Mingyi Hung, The Hong Kong University of Science and Technology (HKUST)
Haifeng You, The Hong Kong University of Science and Technology (HKUST)
Bin Ke, National University of Singapore (NUS)
Bernard Yeung, National University of Singapore (NUS), Southern University of Science and Technology (SUSTech), and Asian Bureau of Finance and Economic Research (ABFER)
Hao Zhou, Southern University of Science and Technology (SUSTech) and Tsinghua University
Xiaoyan Zhang, Tsinghua University