Machine learning (AI) and Quantitative capital management have been a big headline among various articles. A Recent survey from Wall Street Journal also unveils more secrets in the area. We hope to provide a discussion about the current themes in asset management development and the research opportunity from academic perspectives. This research examines the innovation in asset management from both the computer technology and financial services angles and provides examples to integrate machine-learning techniques into financial modeling and to connect data analytics to customer-facing applications. By finishing a loop to include financial instrument creation, we then show a complete scope of technology-based service chain of asset management.
The presentation will examine the current innovation if asset management from two perspectives.  Financial Technology (FinTech) in Asset Management.  Financial Engineering and Machine Learning.
Dr. Peter C. L. Lin is the youngest Industry Professor at Stevens Institute of Technology NJ and he serves as the Director of Financial Analytics MS program. Passionate about quantitative investing, Peter funded Gamma Paradigm, a quantitative investment advisor with a FinTech arm in Asia focusing on AI and data-driven models. Peter began his career as a quantitative analyst at Ryan Labs Asset Management, with $4B asset under management, and as a researcher in quantitative portfolio theories, term-structure models, and alternative investments. Peter received his BS in Computer Science and Information Engineering from National Taiwan University, his MS in Computer Science from Columbia University, and his Ph.D. in Applied Mathematics and Statistics from Johns Hopkins University.