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SoFiE Financial Machine Learning Summer School

"Financial Machine Learning"

July 28 – August 1, 2025

 

The Society for Financial Econometrics (SoFiE) Summer School is an annual week-long research-based course for PhD students, new faculty, and professionals in financial econometrics. For the first two years, the Summer School was held at Oxford University’s Oxford-Man Institute and in 2014 it moved to Harvard University. Since 2017, the SoFiE Financial Econometrics Summer School has taken place in North America, Asia, and Europe. Continuing this successful tradition, the 2025 Summer School at Yale School of Management will foster a rich academic environment for participants to explore and advance the field of financial econometrics.

Course Description

This intensive program is intended for PhD students and researchers in statistics, econometrics, and finance. It covers machine learning and artificial intelligence methods and their application to asset pricing research. The course will discuss the critical role that ML/AI already plays in improving our understanding of finance and economics and discuss the various research growth areas where ML/AI will play a pivotal role in years to come. It will cover theoretical and empirical aspects of high-dimensional models, including the "virtue of complexity," "double descent," and "benign overfit." Next, we will use the problem of return prediction to introduce modeling tools ranging from penalized regression to deep neural networks, followed by a discussion on integrating ML/AI into models of the risk-return tradeoff including applications to factor pricing, stochastic discount factors, and efficient portfolios. Lastly, it will discuss NLP in financial applications using both traditional models (e.g., topic models/LDA) and state-of-the-art large language models.

Course Outline:

  • Mathematical Foundations of Financial Machine Learning
  • The Virtue of Complexity
  • Textual Machine Learning, NLP, LLMs
  • Machine Learning Factor Pricing Models
  • Portfolio Tangent Kernels and Large Factor Models
  • Expected Returns and Alternative Data
  • Convolutional Neural Networks for Finance
  • The Limitations of Financial Machine Learning
  • Artificial Intelligence Pricing Theory
  • AI (Transformer) Asset Pricing Models
  • The final day of the program will consist of a conference featuring new research by guest speakers Mikhail Chernov (UCLA Anderson), Jianqing Fan (Princeton), Stefan Nagel (Chicago Booth), Andreas Neuhierl (Wash. U.), Nikolai Roussanov (Wharton) and Guofu Zhou (Wash. U.).

Course Schedule

SoFiE Schedule

Lecturers

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Bryan T. Kelly (Yale School of Management)

Bryan T. Kelly is the Frederick Frank ’54 and Mary C. Tanner Professor of Finance at the Yale School of Management, a Research Fellow at the National Bureau of Economic Research, Associate Director of SOM’s International Center for Finance, and is the head of machine learning at AQR Capital Management. Professor Kelly’s primary research fields are asset pricing, machine learning, and financial econometrics. He is interested in issues related to expected return, volatility, tail risk, and correlation modeling in financial markets; financial sector systemic risk; financial intermediation; and financial networks. He has served as co-editor of the Journal of Financial Econometrics and associate editor of Journal of Finance and Journal of Financial Economics. Before joining Yale, Kelly was a tenured professor of finance at the University of Chicago Booth School of Business. He earned an AB in economics from University of Chicago, MA in economics from University of California San Diego, and a PhD and MPhil in finance from New York University’s Stern School of Business. Kelly worked in investment banking at Morgan Stanley prior to his PhD.

Dacheng Xiu

Dacheng Xiu (The University of Chicago Booth School of Business)

Dacheng Xiu is Professor of Econometrics and Statistics at the University of Chicago Booth School of Business. His current research focuses on developing machine learning solutions to big-data problems in empirical finance. Xiu’s work has appeared in the Journal of Finance, Review of Financial Studies, Econometrica, Journal of Political Economy, the Journal of the American Statistical Association, and the Annals of Statistics. He has served as Co-Editor for the Journal of Financial Econometrics and has been on the editorial board as an Associate Editor for many prestigious journals, including the Review of Financial Studies, Journal of the American Statistical Association, Journal of Econometrics, and Management Science. He has received several recognitions for his research, including the Fellow of the Society for Financial Econometrics, Fellow of the Journal of Econometrics, AQR Insight Award, EFA Best Paper Prize, and Swiss Finance Institute Outstanding Paper Award. He has been recognized as one of Poets & Quants’ Best 40-under-40 Business School Professors of 2023. Xiu earned his PhD and MA in applied mathematics from Princeton University.

Semyon Malamud

Semyon Malamud (Swiss Finance Institute at EPFL)

Semyon Malamud is an Associate Professor of Finance at the Swiss Federal Institute of Technology in Lausanne and the Director of the Financial Engineering Section. He holds a Senior chair at the Swiss Finance Institute, is a Lamfalussy fellow of the European Central Bank, and a research fellow of the Centre of Economic Policy Research (CEPR) and the Bank for International Settlements.

Semyon's research has been published in top economics and finance outlets, including Econometrica, American Economic Review, Journal of Finance, Review of Financial Studies, and the Journal of Financial Economics. His research has also been recognized with several awards, including the joint INQUIRE Europe-INQUIRE UK prize, the Dauphine-Amundi Chair in Asset Management award, the Europlace Institute of Finance award, and the ETF Academy Award.

Guest Speakers

Mikhail Chernov

Mikhail Chernov, Professor of Finance at the University of California, Los Angeles Anderson School of Management

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Mikhail Chernov (UCLA Anderson School of Management)

Mikhail Chernov is a Professor of Finance at the University of California, Los Angeles Anderson School of Management. His work focuses on macro-based asset pricing, derivatives, fixed income and financial econometrics. “My particular focus is on the importance of market crashes, private and sovereign defaults, and unexpected changes in policy — events that may occur infrequently, but whose impact can be devastating on financial markets and on the economy overall.” Chernov’s academic publications have earned him numerous awards.

Chernov previously served on the faculty of the London School of Economics, London Business School and Columbia Business School. He has held positions at the Bank of England, Federal Reserve Board and the Oxford-Man Institute of Quantitative Finance, and has been a visiting scholar at the Wharton School and NYU Stern School of Business.

Chernov is a research associate at the National Bureau of Economic Research and a research fellow at the Center for Economic and Policy Research. He has served as associate editor of Journal of Business and Economic Statistics, Journal of Econometrics, Journal of Finance, Journal of Financial Econometrics and Journal of Financial and Quantitative Analysis. His professional interests lead him to international cross-disciplinary collaborations in statistics and macroeconomics. Chernov received his PhD from Pennsylvania State University.

Jianqing Fan

Jianqing Fan, Frederick L. Moore '18 Professor of Finance, Professor of Statistics, and Professor of Operations Research and Financial Engineering, Princeton University

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Jianqing Fan (Princeton University)

Jianqing Fan is the Frederick L. Moore '18 Professor of Finance, Professor of Statistics, and Professor of Operations Research and Financial Engineering at Princeton University, where he chaired the department from 2012 to 2015. He is the winner of numerous prizes including the COPSS Presidents' Award, Morningside Gold Medal for Applied Mathematics, Guggenheim Fellow, Pao-Lu Hsu Prize, Guy Medal in Silver, Noether Distinguished Scholar, and Le Cam Award and Lectures. He was elected to Academician from Academia Sinica in 2012 and Royal Flemish Academy of Belgium in 2023.

Professor Fan is interested in statistical theory and methods in data science, statistical machine learning, finance, economics, computational biology, biostatistics with particular skills on high-dimensional statistics, machine learning, spectral methods, neural networks, reinforcement learning, non-parametric modeling, longitudinal and functional data analysis, survival analysis, nonlinear time series, wavelets, among others.

Theis Jensen

Theis Ingerslev Jensen, Assistant Professor of Finance, Yale School of Management

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Theis Ingerslev Jensen (Yale School of Management)

Theis Ingerslev Jensen is an Assistant Professor of Finance at Yale School of Management. Theis' primary research area is empirical asset pricing, where he likes to explore new data sets, especially those related to subjective expectations. His research projects are typically data-intensive and use advanced statistical methods such as machine learning.

Theis grew up in Denmark where he obtained his Ph.D. in financial Economics from Copenhagen Business School in 2023.

Stefan Nagel

Stefan Nagel, Fama Family Distinguished Service Professor of Finance, University of Chicago Booth School of Business

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Stefan Nagel (The University of Chicago Booth School of Business)

Stefan Nagel is the Fama Family Distinguished Service Professor of Finance at Chicago Booth. His research focuses on asset pricing, investor behavior, and the formation of investor expectations. His most recent work explores the role of personal experiences in shaping expectations about the macroeconomy and financial market returns, models of investor learning about long-run growth with decaying memory, and the application of machine learning techniques to understand the risk and return of investment strategies in the stock market. Nagel has won various awards for his research, among them the Smith-Breeden Prize of the American Finance Association for the best paper in the Journal of Finance in 2004 and the Fama/DFA prize for the best asset pricing paper in the Journal of Financial Economics in 2006 and 2020 (first prize) and 2010 (second prize).

Professor Nagel served as Executive Editor of the Journal of Finance, one of the leading academic finance journals in the world, from 2016 to 2022. Previously, he was an editor at the Review of Financial Studies from 2014-2015 and an associate editor at various top journals. He is also a research associate at the National Bureau of Economic Research (Cambridge, MA) and a research fellow at the Centre for Economic Policy Research (London, UK) and CESifo (Munich, Germany). He is vice-president of the Western Finance Association.

Before joining Booth, Nagel taught at the University of Michigan's Ross School of Business (2013-17), Stanford Graduate School of Business (2004-13) and in the Economics Department at Harvard University (2003-04). He received his PhD from the London Business School in 2003 and his Diplom (M.S. equiv.) in Business Economics from the University of Trier (Germany) in 1999.

Andreas Neuhierl

Andreas Neuhierl, Assistant Professor of Finance, Olin Business School at Washington University in St. Louis

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Andreas Neuhierl (Olin Business School at Washington University in St. Louis)

Andreas Neuhierl is an Assistant Professor of Finance at the Olin Business School at Washington University in St. Louis. He received his PhD and MS in Finance from Northwestern (Kellogg). Prior to joining Olin, he was on the faculty of the University of Notre Dame and held visiting appointments and the University of Chicago Booth School of Business. His research interests include empirical asset pricing, financial econometrics, macroeconomics and commodity markets. Specifically, recent research has examined the role of monetary policy for equity markets and the use of machine learning methods for financial prediction problems.

Nikolai Roussanov

Nikolai Roussanov, Moise Y. Safra Professor and Professor of Finance, Wharton School, University of Pennsylvania

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Nikolai Roussanov (The Wharton School, University of Pennsylvania)

Nikolai Roussanov is Moise Y. Safra Professor and Professor of Finance at the Wharton School, University of Pennsylvania, and Research Associate at the National Bureau of Economic Research. His research focuses on areas of interaction between asset pricing and macroeconomics, ranging from equity to fixed income, currency, and commodity markets, to entrepreneurship and individual financial behavior. His articles have been published in the Journal of Finance, Quarterly Journal of Economics, Journal of Financial Economics, Review of Financial Studies, Journal of Monetary Economics, and Management Science, and won a number of prizes, including the 2015 AQR Insight Award. He currently serves as Co-Editor of the Journal of Financial Economics and has in the past served on editorial boards of the Journal of Finance and Journal of Monetary Economics, as Editor of the Review of Asset Pricing Studies, and President of the Macro Finance Society. At Wharton he has taught courses on Behavioral Finance, Fixed Income Securities, and Consumer Financial Decision Making to undergraduate and MBA students, as well as Empirical Methods in Finance aimed at students in the doctoral program.

Roussanov received an undergraduate degree in mathematics from Harvard College and a Ph.D. in Finance from the University of Chicago.

Yinan Su

Yinan Su, Assistant Professor of Finance, Johns Hopkins University Carey Business School

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Yinan Su (Johns Hopkins University Carey Business School)

Yinan Su is an Assistant Professor of Finance at the Johns Hopkins University Carey Business School. His research interests include banking, asset pricing, financial econometrics, and economic networks. Before joining Carey, Yinan Su earned his PhD degree from the University of Chicago's Joint Program in Financial Economics and a bachelor's degree in economics and finance from Tsinghua University.

Guofu Zhou

Guofu Zhou, Frederick Bierman and James E. Spears Professor of Finance, Olin Business School at Washington University in St. Louis

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Guofu Zhou (Olin Business School at Washington University in St. Louis)

Guofu Zhou is the Frederick Bierman and James E. Spears Professor of Finance at Olin Business School at Washington University in St. Louis. His research interest include investment strategies, big data, machine learning, forecasting, technical analysis, asset allocation, anomalies, asymmetric information, asset pricing tests and econometric methods. His journal publications have appeared in Journal of Finance, Journal of Financial Economics, Review of Financial Studies, Journal of Financial and Quantitative Analysis, Management Science, and other leading academic journals. He is also a co-author of Financial Economic, and contributor to several books, including Advanced Fixed-Income Valuation Tools, and Q-finance, etc. Presently, he also serves as Associate Editor of Journal of Financial and Quantitative Analysis, and on the Editorial Board of Journal of Portfolio Management, International Journal of Portfolio Analysis & Management, Annals of Economics and Finance.

Professor Zhou holds a BS degree from Chengdu College of Geology, a MS in Computational Mathematics from Chengdu Branch, Academia Sinica, and a PhD in Economics from Duke University.

Applications

Applicants should register and submit electronic materials through the following website: https://yalesurvey.ca1.qualtrics.com/jfe/form/SV_6DwdFsgYPl6D5xs. Applications should include a full CV and motivation letter (half-page length) explaining why attending this course would be helpful to the applicant’s research work. All materials should be in PDF format. The application deadline is May 16, 2025

Fees

Students: $500
Faculty: $750
Professionals: $1,250 

Admission of a selected applicant will be conditional on the fee payment (details will be provided in the admission email). Fees cover the course; breakfast, lunch and coffee breaks during the program; and a closing reception.

Travel and accommodation: Attendees are responsible for their own travel and accommodation costs. 

Lodging

Airport Transportation

Useful Links

For questions, please reach out to karen.spitzer@yale.edu.

All accepted participants are expected to be members of the Society for Financial Econometrics before their admission is confirmed. Visit https://www.stern.nyu.edu/experience-stern/about/departments-centers-initiatives/centers-of-research/volatility-and-risk-institute/sofie/sofie-membership for instructions on how to join the society ($10 student membership).