Speakers
Markus Leippold
(UZH)
Qian Wang
(UZH)
Description
Processing financial documents quickly and incorporating updated information (e.g. earning calls, news and financial filings) are the keys to successful investment decision. However, as the volume of financial documents explodes, the number of financial analysts is far from enough compared with the demand for efficiency and coverage, especially during peak seasons. With the progress of Natural Language Processing (NLP), extracting valuable information from these financial text sources gain popularity among academic and industrial researchers. This talk would first provide an overview of common datasets that are public available in the field (both labeled and unlabeled), and then cover some of our researches using these datasets.
