Abstract:The financial industry is undergoing a significant transformation, transitioning from a model-driven approach to a data-driven one, thanks to the advent of big data. In this era, machine learning and artificial intelligence techniques are playing an increasingly crucial role in revolutionizing various aspects of financial services within the Fintech domain. This presentation aims to delve into our latest research findings in Fintech, covering a wide array of topics such as trading, option pricing, corporate finance, smart contracts, and P2P lending.

We will explore cutting-edge artificial intelligence techniques employed in high-frequency trading (HFT), including marker discovery, trading dynamics retrieval, and cryptocurrency price discovery. Additionally, we will introduce innovative machine learning methods for implied volatility pricing and a model-driven approach known as Ultima pricing for European options. Furthermore, our talk will showcase a novel and interpretable deep learning model designed to forecast stock excess returns using SEC 8-K text data.

Finally, we will provide a brief overview of the first-ever protocol utilizing smart contracts to exploit the financial market, as well as a quantum machine learning (QML) solution for addressing imbalanced credit risk prediction. By examining these breakthroughs, we aim to shed light on the advancements made in the realm of Fintech and the pivotal role played by artificial intelligence in shaping the future of finance.

Short Bio:Dr. Henry Han isMcCollum Endowed Chair in Data Science and Professor of Computer Science in the School of Engineering and Computer Science at Baylor University. His research interests are in Data science, AI, Fintech, informatics, and quantum machine learning. He has published more than 130 papers in leading journals and conferences in Data science and AI fields. He was professor of computer science at Fordham University as well as the founding director of Fordham’s Cybersecurity program. He has supervised more than 70 students including post-docs, Ph.D., MS, and undergraduate students. His research is supported by NSF, NIH, and NASA