The Society for Financial Econometrics (SoFiE) Summer School returned to NYU Shanghai from August 19 to 23, welcoming 98 young scholars from across Europe, North America, and Asia. This year marked the seventh summer school hosted by the Volatility Institute at NYU Shanghai (VINS), and the first held at the New Bund campus. The theme of this year’s summer school, Financial Machine Learning, was chosen to echo the growing importance of machine learning and artificial intelligence in transforming financial research and practice.
The week-long program featured intensive lectures, interactive discussions, and participant presentations led by three world-renowned experts in the field: Professor Dacheng Xiu from the University of Chicago, Professor Bryan Kelly from Yale School of Management, and Professor Semyon Malamud from the Swiss Federal Institute of Technology in Lausanne. The lectures covered a broad range of topics, including machine learning factor models, high-dimensional regressions, random matrix theory, and the application of neural networks in finance.
Professor Dacheng Xiu
Professor Xiu’s sessions focused on measuring expected returns using alternative data sources, such as text and images, through machine learning models, fostering new ideas in the field of financial machine learning. He also explored the limitations of machine learning when dealing with weak signals and rare alphas, providing participants with a critical understanding of the strengths and challenges in this emerging field.
Professor Bryan Kelly
Professor Kelly introduced the fundamentals of financial machine learning and delved into complex topics like Instrumented Principal Component Analysis and Auto Encoded Asset Pricing models. He then shared his research on the virtue of complexity in return prediction and explored the use of textual analysis in finance and economics.
Professor Semyon Malamud
Professor Malamud delivered lectures on regressions in high dimensions and random matrix theory, effectively integrating theoretical concepts with relevant coding examples to enhance participants’ understanding. The following day, he presented his research on neural tangent kernels, neural networks, the curse of dimensionality, portfolio tangent kernels, and large factor models.
After several years of remote sessions, the return to an offline format was met with enthusiasm by both participants and instructors. “Hosting the summer school at our New Bund campus not only enhanced the learning experience but also fostered a sense of community among participants,” said Zhou Xin, the executive director of VINS. He added that the onsite format facilitated greater interaction, collaboration, and idea exchange, essential elements for a successful academic gathering.
The 2024 cohort was distinguished by its diversity, with participants hailing from prestigious institutions such as Cornell University, the University of Cambridge, Carnegie Mellon University, Monash University, Peking University, and Shanghai Jiao Tong University, as well as the Federal Reserve Bank of San Francisco. This mix of academic scholars and industry practitioners enriched the discussions and provided a wide array of perspectives on the subject matter.
Participants praised the course structure and the expertise of the lecturers. “The course was exceptionally well-structured, offering a deep dive into the application of machine learning and AI in finance,” said Zhao Liu, Assistant Professor of Finance at the University of Warwick. “The hands-on approach shared by the lecturers to understanding advanced financial models was particularly beneficial, equipping me with skills that will be essential for my future academic work,” he added. Vladislav Pyzhov, a PhD student from the University of Technology Sydney, highlighted the practical components of the course, sharing, “The focus on actual research papers rather than purely theoretical content was refreshing and highly beneficial.”
The Society for Financial Econometrics (SoFiE) Financial Econometrics Summer School is a week-long research-based course in statistics, econometrics, and finance aimed at PhD students, researchers, and junior faculty. The summer school, held yearly at academic institutions around the world, including Oxford, Harvard, and the Kellogg School of Management at Northwestern University, has been held at NYU Shanghai seven times.