Joint Webinar with Inquire UKPrize Winners
Professor Lin Cong will present on how to optimize investment objectives by using reinforcement learning.
We will be kicking off 2021 with our next webinar organized jointly with Inquire UK. Professor Lin William Cong, Cornell University, will present his research paper, “Single-Step Portfolio Construction through Reinforcement Learning and Economically Interpretable AI.“
Date: 13 January 2021
Time: 16:00 CET
Registration: Click here
Professor Cong and his co-authors propose direct optimization of investors' objectives via reinforcement learning. This is an alternative to the widely-adopted two-step portfolio-management paradigm which entails estimating distributions of asset returns. Building on recent breakthroughs in AI, they develop neural-network-based multi-sequence models which are tailored to various distinguishing features of economic and financial data.
The resulting AlphaPortfolio yields stellar, out-of-sample performances (e.g., Sharpe ratio above two) that are robust under various economic and trading restrictions. Moreover, they use polynomial-feature-sensitivity and textual-factor analyses to project the model onto linear regression; natural language spaces uncover key market signals that drive investment performance.
Overall, the authors highlight the utility of reinforcement deep learning in social sciences, especially finance, and provide novel "economic distillation'' procedures for interpreting AI and big data models.
About the presentor:
Lin William Cong is the Rudd Family Professor of Management and Associate Professor of Finance at the Johnson Graduate School of Management at Cornell
University, where he directs the FinTech Initiative. He is also a Kauffman Junior Fellow, Poets & Quants World Best Business School Professor, advisor to the Wall Street Blockchain Alliance, Luohan Academy Fellow, and serves as editor or associate editor at several leading journals such as Management Science.
Prior to joining Cornell, he was an assistant professor of Finance at the University of Chicago Booth School of Business, faculty member at the Center for East Asian Studies, doctoral fellow at the Stanford Institute for Innovation in Developing Economies, and George Shultz Scholar at the Stanford Institute for Economic Policy Research.
Professor Cong’s research spans financial economics, information economics, FinTech and Economic Data Science, and Entrepreneurship (theory and intersection with
digitization and development). Professor Cong has received numerous accolades such as the AAM-CAMRI-CFA Institute Prize in Asset Management, the CME Best paper Award, Finance Theory Group Best Paper Award, the Shmuel Kandel Award, and has also been invited to speak at venture funds, technology firms, investment and trading shops, and government agencies such as IMF, Asset Management Association of China, SEC, and federal reserve banks. He received his Ph.D. in Finance and MS in Statistics from Stanford University, and A.M. in Physics jointly with A.B. in Math and Physics from Harvard University.