Connecting AI Innovation and Finance Through Research, Education, and Practice
The Wharton AI in Finance Lab brings together expertise in finance, AI, and analytics to advance research, education, and practice. Led by Wharton finance faculty and supported by the Wharton AI & Analytics Initiative, the Lab develops AI-enabled data infrastructure, advances innovative teaching, and fosters collaboration between academia and industry to shape the future of finance.
Advancing AI Research in Finance
Generating rigorous, interdisciplinary research at the intersection of AI and financial economics.
Building
AI-Enabled
Infrastructure
Creating the data, tools, and computational resources that power AI-enabled finance.
Driving Teaching Innovation
Transforming how AI is taught across finance education.
Engaging Students & Practitioners
Building a community connecting students, faculty, and industry practitioners at the AI-finance frontier.
Advancing AI Research in Finance
Research Projects
Reinforcement Learning and Autonomous AI in Financial Markets
Reinforcement learning, and autonomous learning algorithms more broadly, enable AI systems to discover strategies through trial-and-error interaction with financial markets rather than relying solely on rules specified in advance. We study how these self-learning, adaptive systems trade, make markets, manage portfolios, and control risk, as well as how they interact strategically with human and algorithmic market participants. Our research identifies when autonomous learning improves performance and market efficiency, when it produces unintended behaviors such as algorithmic herding, market manipulation, or collusive outcomes, and how these behaviors affect market fragility, price informativeness, and liquidity, providing an economic foundation for the design, regulation, and deployment of autonomous financial AI.
LLM Reasoning for Financial AI Agents
We develop financial AI agents that move beyond one-shot prediction and direct-answer generation by reasoning through complex, information-intensive decisions. These agents use large language models to interpret diverse financial information, decompose problems into sequential steps, form and evaluate competing hypotheses, use analytical tools, and coordinate specialized workflows. We study how reasoning, retrieval, memory, verification, and multi-agent collaboration can make their decisions more accurate, reliable, auditable, and economically valuable.
Featured Papers
AI-Powered Trading
There is no evidence yet of AI collusion hurting the financial markets, but the threat is real, warns a paper co-authored by Wharton’s Winston Wei Dou and Itay Goldstein.
From the Reinforcement Learning and Autonomous AI in Financial Markets project.
Read the paper: AI-Powered Trading, Algorithmic Collusion, and Price Efficiency →
Building AI-Enabled Infrastructure
World Synthetic Markets
The World Synthetic Markets project builds interactive financial-market simulations designed to reproduce the key institutions, strategic interactions, and feedback mechanisms of real-world trading using models grounded in established principles of finance.
Within these environments, autonomous AI trading systems and models of diverse market participants, including investors, intermediaries, and financial institutions, learn, trade, and adapt to one another.
These “financial wind tunnels” enable controlled and repeatable experiments that would be impractical or impossible in live markets, allowing researchers to uncover emergent market dynamics, stress-test AI strategies and financial systems, and evaluate how new technologies, regulation, and market design shape liquidity, price discovery, financial stability, and welfare.
AI-Ready Financial Datasets
In partnership with Wharton Research Data Services, Penn Libraries, and Wharton Computing, the Lab is building integrated, point-in-time datasets that link traditional financial data with financial and business text, products, patents, supply chains, brands, trademarks, networks, and individual decision-makers.
At its core is the development of reliable linking tables across financial databases and structured and unstructured data sources. Initial areas of focus include financial and business text; products, patents, and supply chains; brands and trademarks; firm and market characteristics; and fund managers.
The resulting infrastructure will provide faculty and students with a shared foundation for empirical research, classroom applications, and the development and evaluation of financial AI tools.
Help Build the Future of AI-Ready Financial Data
The Wharton AI in Finance Lab welcomes partnerships with faculty and organizations that can contribute data, expertise, and resources to help develop integrated, research-grade datasets for AI-driven financial research and student experiential learning.
Contact ai-finance@wharton.upenn.edu for more information.
Driving Teaching Innovation
Course Spotlight: AI and Data Science in Finance
How Wharton Is Preparing Students for an AI-Driven Financial Future
As AI reshapes financial markets, Wharton is preparing students to do more than use the latest tools. They’re learning how to think critically about AI’s role in finance. In AI and Data Science in Finance, Associate Professor Winston Dou connects cutting-edge research with real-world financial challenges, from autonomous trading to market prediction. See how students are building the skills to navigate an AI-driven financial future and how those ideas are helping shape the vision for the Wharton AI in Finance Lab.
Engaging Students & Practitioners
Explore the Wharton AI in Finance Lab’s lastest events for students and practitioners.
Fireside Chat: Jason Wright, WG’00, Apax Partners
October 13, 2026 — SHDH 350 | Open to students
Join Jason Wright, WG’00, Equity Partner at Apax and member of Wharton’s Graduate Executive Board, for a fireside chat with Winston Dou, associate professor of finance at the Wharton School and faculty director of the Wharton AI in Finance Lab.
Together, they’ll explore how AI is changing the financial landscape, how Apax is navigating this pivotal moment, and what these shifts could mean for the future of finance and private equity.
Podcast
Hosted by Professor Itay Goldstein, the third season of Future of Finance gathers leading scholars, experts from the industry, and regulatory officials to explore the different ways AI is changing the financial landscape. Through four episodes, Professor Goldstein and his guests will examine AI’s impact on quantitative finance, markets and the economy, policy and regulation, and the future of financial services. Join us as we dive into the opportunities and challenges presented by the AI revolution.
Faculty Leadership
Winston Wei Dou
Associate Professor of Finance
Faculty Director, Wharton AI in Finance Lab
Bio
Professor Winston Wei Dou (窦炜) is a financial economist, Associate Professor of Finance, and Golub Faculty Scholar at the Wharton School of the University of Pennsylvania. He also serves as Director of the Wharton AI in Finance Lab. His work bridges frontier academic research, investment-industry practice, and financial regulation, including recent research on applications of AI and modern data science to financial decision-making and their broader consequences for financial markets.
Before joining Wharton, he earned a Ph.D. in Financial Economics at MIT and a Ph.D. in Statistics from Yale University. He received his primary B.S. degree in Pure Mathematics, along with a B.S. in Economics, from Peking University.
Professor Dou has been a Research Associate at the National Bureau of Economic Research (NBER) since 2025, after serving as a NBER Faculty Research Fellow from 2022 to 2025. He was a Fama-Miller visiting professor at the Chicago Booth School of Business during the winter term of 2023. He is also a fellow at the Asian Bureau of Financial and Economic Research (ABFER). His research has received numerous awards from leading academic conferences and professional associations.
His research examines how strategic behavior, market power, organizational structure, and technological innovation shape asset prices and the functioning of capital markets. Centered on asset pricing and capital markets, his work integrates ideas and methods from industrial organization, macroeconomics, econometrics, and artificial intelligence. He develops innovative theoretical models, connects them rigorously to data, and places particular emphasis on model robustness.
One central strand of his research studies strategic competition in product and financial markets, including market power, tacit collusion, and implicit coordination. Drawing on modern industrial organization, this work shows how strategic interactions among firms, investors, and financial intermediaries shape asset prices, market liquidity, information production, risk, and broader capital market dynamics.
Building on this foundation, his recent research investigates how modern AI is transforming strategic behavior in financial markets. It examines how AI-powered market participants learn, compete, coordinate, and potentially manipulate markets, and how these behaviors affect price efficiency, information aggregation, liquidity, competition, and financial stability. This line of research derives implications for financial regulation and policy, market design, disclosure and information design, and the production and use of information in financial markets.
Senior Affiliated Faculty
Itay Goldstein
Joel S. Ehrenkranz Family Professor
Professor of Finance
Professor of Economics
Chairperson, Finance Department
Academic Director, Wharton Future of Finance Initiative
Bio
Itay Goldstein is the Joel S. Ehrenkranz Family Professor and a Professor of Finance at the Wharton School of the University of Pennsylvania, and an Academic Director of the Wharton Future of Finance Initiative. He has been on the faculty of the Wharton School since 2004 and holds a secondary appointment as a Professor of Economics.
Professor Goldstein currently serves as the Chairperson of the Finance Department. Prior to that, he was the coordinator of the PhD. program in Finance and, in 2022, received the Provost’s Award for Distinguished PhD Teaching and Mentoring.
Professor Goldstein earned his PhD in Economics in 2001 from Tel Aviv University. He is an expert in the areas of corporate finance, financial institutions, and financial markets, focusing on financial fragility and crises and on the feedback effects between firms and financial markets. His research has been published in top academic journals, including the American Economic Review, the Journal of Finance, the Journal of Financial Economics, the Journal of Political Economy, the Review of Economic Studies, and the Review of Financial Studies. His research has also been featured in the Economist, Wall Street Journal, Financial Times, Bloomberg, Forbes, National Public Radio, and other popular press.
Professor Goldstein was the Executive Editor of the Review of Financial Studies from 2018 to 2024. He is a Research Associate at the National Bureau of Economic Research. He was the co-founder and the first president of the Finance Theory Group, served as a director of the American Finance Association, the Western Finance Association, and the Financial Intermediation Research Society, and is now the Vice President of the Western Finance Association.
Professor Goldstein has served as an academic advisor in various policy institutions, including the Federal Reserve Banks of New York, Philadelphia, and Richmond, the Bank of Canada, the Bank for International Settlements, the Committee for Capital Markets Regulation, and the International Monetary Fund. He is a frequent speaker in academic and policy forums around the world and has been a keynote speaker in leading academic conferences.
His full website is available here.
Michael Roberts
William H. Lawrence Professor
Professor of Finance
Vice Dean, Wharton MBA Program
Bio
Michael R. Roberts is the Vice Dean of the MBA program, William H. Lawrence Professor, and Professor of Finance at The Wharton School of the University of Pennsylvania. Professor Roberts is also a Research Associate of the National Bureau of Economic Research, and an affiliate of the Institute for Law and Economics and the Wharton AI and Analytics Initiative.
Professor Roberts’ research spans corporate finance, banking, and investments. He has examined corporate financial and investment policies, the structure of syndicated loans, equity pricing anomalies, collateralized loan obligation (CLO) performance, machine learning applications in investment banking, and AI usage in financial literacy. His research has amassed over 20,000 citations and has received numerous awards including two Brattle Prizes for Distinguished Paper published in the Journal of Finance, a Jensen Prize for best paper on Corporate Finance and Organizations published in the Journal of Financial Economics, and the Jack Treynor Prize from the Institute for Quantitative Research in Finance. Professor Roberts has served on many journal editorial boards, including the Journal of Finance of which he was a co-editor.
In addition to his research, Professor Roberts is an acclaimed teacher. At The Wharton School, his accolades include fourteen separate teaching awards, including the David W. Hauk Award and multiple nominations for the Helen Kardon Moss Anvil Teaching Award. While at Duke University, he won the Daimler-Chrysler Core Teaching Award at the Fuqua School of Business. He has taught undergraduate, MBA, Ph.D., and executive education courses in Finance, Economics, Statistics, and Data Science. Outside of academia, Professor Roberts has worked as a financial engineer and consultant, providing services to many financial and nonfinancial corporations as well as expert testimony in corporate legal matters.
Professor Roberts earned his B.A. in Economics from the University of California at San Diego, and his M.A. in Statistics and Ph.D. in Economics from the University of California at Berkeley.
Fellows
Fernando Stein, PhD Student
The Wharton School
Yuecheng Su, PhD Student
The Wharton School
Ruijin Liu, PhD Student
The Hong Kong University of Science and Technology
Affiliated Students
In the News
September 29, 2026 | AI Street
How Agents Learn to Manipulate Markets: Study
February 16, 2026 | Finance at Wharton
Itay Goldstein on AI’s Opportunity and Risk in Finance
July 30, 2025 | Bloomberg
‘Dumb’ AI Bots Collude to Rig Markets, Wharton Research Finds
June 30, 2025 | Bloomberg
The Bots Will Work Together
June 17, 2024 | Knowledge at Wharton
The Impact of AI on the Finance Sector
Harnessing the Power of Partnership
We welcome partnerships with companies seeking to apply AI-enabled data science to real-world problems.
If you are interested in collaborating with us, please contact Tania Rorke, Senior Associate Director of Corporate & Donor Engagement, Wharton AI & Analytics Initiative.
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