2318 Steinberg-Dietrich Hall
3620 Locust Walk
Philadelphia, PA 19104
Links: CV, Personal Website
Professor Winston (Wei) Dou is an Assistant Professor of Finance and the Golub Faculty Scholar at the Wharton School, University of Pennsylvania. He is a financial economist specializing in asset pricing, capital markets, industrial organization (IO), macroeconomics, and econometrics. His research primarily focuses on asset pricing and capital markets, integrating concepts, insights, modeling, and empirical tools from IO, macroeconomics, and econometrics. Professor Dou is dedicated to developing innovative theoretical models and establishing strong connections between these models and data, with a particular emphasis on model robustness.
Professor Dou’s work is among the pioneering contributions to understanding the impact of strategic competition in both product and asset markets, such as tacit collusion and implicit coordination, on asset pricing and capital market dynamics. His work draws heavily on modern IO literature, which highlights the market power of industry leaders through strategic competition tactics, such as tacit collusion and coordination, across various industries. Additionally, his work explores the impact of AI technologies on financial markets and the associated regulatory measures.
Since joining Wharton, Professor Dou has taught three distinct courses across the undergraduate, MBA, and doctoral programs. He teaches one course on the derivatives markets for the undergraduate and MBA programs, and two different full-fledged courses for the doctoral program, focusing on Asset Pricing, Capital Markets, and Macro Finance. He has received the teaching excellence award at the Wharton School.
His research has been published in leading academic journals such as Econometrica, The Journal of Finance, The Journal of Financial Economics, The Review of Financial Studies, The Annals of Statistics, The Journal of the American Statistical Association, and Management Science. He currently serves as the Associate Editor of The Review of Finance, The Journal of Corporate Finance, and The Journal of Economic Dynamics and Control.
Professor Dou has been a faculty research fellow at the National Bureau of Economic Research (NBER) since 2022, and he was a Fama-Miller visiting professor at the Chicago Booth School of Business during the winter term of 2023. He has won numerous awards for his research at conferences and professional associations, including the NASDAQ Award for the Best Paper on Asset Pricing at the Western Finance Association (WFA), the AAII Award for the Best Paper on Investments at the Midwestern Finance Association (MFA), the Best Paper Award on Asset Pricing at the Northern Finance Association (NFA), the Best Paper Award at the Red Rock Finance Conference, the I. R. Savage Award by the American Statistical Association (ASA), the Richard A. Crowell Memorial Prize at PanAgora Asset Management, the CFA Institute Asia-Pacific Research Exchange Award, the Best Paper Award at the China International Conference in Macroeconomics (CICM), the Best Paper Award at the Melbourne Asset Pricing Meeting, the Jacob Gold & Associates Best Paper Prize at the ASU Sonoran Winter Finance Conference, and the IRF Best Paper Award at the Asian Finance Association. At the Wharton School, his research has also earned several awards, including the Marshall Blume Prize, the Jacobs Levy Prize, the Dean’s Research Fund Award (twice), and the Golub Faculty Scholar Award (twice).
Before joining Wharton, he completed his dissertation and received his doctoral degree in financial economics at MIT, and received another doctoral degree in statistics from Yale University. He obtained a B.S. in mathematics (primary) and another B.S. in economics from Peking University in China.
Link to Personal Webpage of Research
Winston Wei Dou, Yan Ji, David Reibstein, Wei Wu (2021), Inalienable Customer Capital, Corporate Liquidity, and Stock Returns, Journal of Finance, 1 (76).
Winston Wei Dou, Yan Ji, Michael Weber (Work In Progress), Monetary Policy, Competition, and Asset Prices.
Winston Wei Dou and Yicheng Zhu (Work In Progress), Overshooting, Slow Recovery, and Asset Prices.
Winston Wei Dou, Leonid Kogan, Renwei Wu (Work In Progress), Delegated Portfolio Choice: Asset Pricing with Fund Flows.
Winston Wei Dou, Hui Chen, Leonid Kogan (Under Revision), Measuring “Dark Matter\.
Winston Wei Dou, Hui Chen, Hongye Guo, Yan Ji (Working), Feedback and Contagion through Distressed Competition.
Winston Wei Dou and Yan Ji (Under Revision), External Financing and Customer Capital: A Financial Theory of Markups.
Winston Wei Dou, Xu Cheng, Zhipeng Liao (Working), Robust Evaluations of Asset Pricing Models.
Winston Wei Dou, Luke Taylor, Wei Wang, Wenyu Wang (Working), Dissecting Bankruptcy Frictions.
Winston Wei Dou, Yan Ji, Renwei Wu (Under Revision), Competition, Profitability, and Risk Premia.
Link to Personal Webpage of Teaching
FNCE934 – ADVANCED TOPICS IN DYNAMIC ASSET PRICING (FALL 2017)
This course has three main objectives:
The first object is to introduce students to the fundamental works and the frontier of research in dynamic asset pricing. We will cover recent models that have been proposed to shed light on intriguing and important empirical patterns in the cross section and in the time series. Topics include non-separable utilities, market incompleteness, learning, uncertainty, differences of opinions, ex-ante and ex-post asymmetric information, ambiguity and Knightian uncertainty.
The second objective is to teach students how to think of asset pricing research under a bigger or richer framework. We shall focus on the interactions between asset pricing and other fields such as macroeconomics, corporate finance, financial institutions, and international finance. The goal of investigating the joint dynamics is not only to better understand how asset prices are determined, but also (maybe more importantly) how would asset pricing dynamics affect other important economic variables such as investment, corporate payout and financing, unemployment, risk sharing, and international capital flows. The students will learn production-based asset pricing models, particularly the asset pricing models with investment-specific technology shocks, uncertainty shocks, risk shocks, financial frictions, searching frictions, and information frictions. Of course, the advanced solution methods will the focus too.
The third objective is to introduce advanced empirical methods to analyze the data and the quantitative dynamic models. It includes how to estimate structural dynamic models, how to evaluate structural models beyond goodness-of-fit tests, how to confront the models’ predictions with empirical data by simulation and re-sampling techniques, and how to efficiently test models and explore new patterns using asset pricing and macro data.
FNCE206 – FINANCIAL DERIVATIVES (SPRING 2017)
This course covers one of the most exciting yet fundamental areas in finance: derivative securities. In the modern financial architecture, financial derivatives can be the most challenging and exotic securities traded by institutional specialists, while at the same time, they can also be the basic securities commonly traded by retail investors such as S&P 500 Index Options. Beyond trading, the basic ideas of financial derivatives serve as building blocks to understand a much broader class of financial problems, such as complex asset portfolios, strategic corporate decisions, and stages in venture capital investing.
The global derivatives market is one of the most fast-growing markets, with over $600 trillion notional value in total. It is as important as ever to understand both the strategic opportunities offered by these derivative instruments and the risks they imply.
The main objective of this course is to help students gain the intuition and skills on (1) pricing and hedging of derivative securities, and (2) using them for investment and risk management. In terms of methodologies, we apply the non-arbitrage principle and the law of one price to dynamic models through three different approaches: the binomial tree model, the Black-Scholes-Merton option pricing model, and the simulation-based risk neutral pricing approach.
We discuss a wide range of applications, including the use of derivatives in asset management, the valuation of corporate securities such as stocks and corporate bonds with embedded options, interest rate derivatives, credit derivatives, as well as crude oil derivatives. In addition to theoretical discussions, we also emphasize practical considerations of implementing strategies using derivatives as tools, especially when no-arbitrage conditions do not hold.
This course covers one of the most exciting and fundamental areas in finance. Financial derivatives serve as building blocks to understand broad classes of financial problems, such as complex asset portfolios, strategic corporate decisions, and stages in venture capital investing. The main objective of this course is build intuition and skills on (1) pricing and hedging of derivative securities, and (2) using them for investment and risk management. In terms of methodologies, we apply the non-arbitrage principle and the law of one price to dynamic models through three different approaches: the binomial tree model, the Black-Scholes-Merton option pricing model, and the simulation-based risk neutral pricing approach. The course covers a wide range of applications, including the use of derivatives in asset management, the valuation of corporate securities such as stocks and corporate bonds with embedded options, interest rate and credit derivatives, as well as crude oil derivatives. We emphasize practical considerations of implementing strategies using derivatives as tools, especially when no-arbitrage conditions do not hold. STAT 1020 may be taken concurrently.
FNCE2170001 ( Syllabus )
The objective of this course is to undertake a rigorous study of the theoretical foundations of modern financial economics. The course will cover the central themes of modern finance including individual investment decisions under uncertainty, stochastic dominance, mean variance theory, capital market equilibrium and asset valuation, arbitrage pricing theory, option pricing, and incomplete markets, and the potential application of these themes. Upon completion of this course, students should acquire a clear understanding of the major theoretical results concerning individuals' consumption and portfolio decisions under uncertainty and their implications for the valuation of securities.
FNCE9110001 ( Syllabus )
This course covers one of the most exciting and fundamental areas in finance. Financial derivatives serve as building blocks to understand broad classes of financial problems, such as complex asset portfolios, strategic corporate decisions, and stages in venture capital investing. The main objective of this course is build intuition and skills on (1) pricing and hedging of derivative securities, and (2) using them for investment and risk management. In terms of methodologies, we apply the non-arbitrage principle and the law of one price to dynamic models through three different approaches: the binomial tree model, the Black-Scholes-Merton option pricing model, and the simulation-based risk neutral pricing approach. The course covers a wide range of applications, including the use of derivatives in asset management, the valuation of corporate securities such as stocks and corporate bonds with embedded options, interest rate and credit derivatives, as well as crude oil derivatives. We emphasize practical considerations of implementing strategies using derivatives as tools, especially when no-arbitrage conditions do not hold. STAT 1020 may be taken concurrently.
Integrates the work of the various courses and familiarizes the student with the tools and techniques of research.
This course covers one of the most exciting and fundamental areas in finance. Financial derivatives serve as building blocks to understand broad classes of financial problems, such as complex asset portfolios, strategic corporate decisions, and stages in venture capital investing. The main objective of this course is build intuition and skills on (1) pricing and hedging of derivative securities, and (2) using them for investment and risk management. In terms of methodologies, we apply the non-arbitrage principle and the law of one price to dynamic models through three different approaches: the binomial tree model, the Black-Scholes-Merton option pricing model, and the simulation-based risk neutral pricing approach. The course covers a wide range of applications, including the use of derivatives in asset management, the valuation of corporate securities such as stocks and corporate bonds with embedded options, interest rate and credit derivatives, as well as crude oil derivatives. We emphasize practical considerations of implementing strategies using derivatives as tools, especially when no-arbitrage conditions do not hold.
Independent Study Projects require extensive independent work and a considerable amount of writing. ISP in Finance are intended to give students the opportunity to study a particular topic in Finance in greater depth than is covered in the curriculum. The application for ISP's should outline a plan of study that requires at least as much work as a typical course in the Finance Department that meets twice a week. Applications for FNCE 8990 ISP's will not be accepted after the THIRD WEEK OF THE SEMESTER. ISP's must be supervised by a Standing Faculty member of the Finance Department.
The objective of this course is to undertake a rigorous study of the theoretical foundations of modern financial economics. The course will cover the central themes of modern finance including individual investment decisions under uncertainty, stochastic dominance, mean variance theory, capital market equilibrium and asset valuation, arbitrage pricing theory, option pricing, and incomplete markets, and the potential application of these themes. Upon completion of this course, students should acquire a clear understanding of the major theoretical results concerning individuals' consumption and portfolio decisions under uncertainty and their implications for the valuation of securities.
This course has three main objectives: The first object is to introduce students to the fundamental works and the frontier of research in dynamic asset pricing. We will cover recent models that have been proposed to shed light on intreguing and important empirical patterns in the cross section and in the time series. Topics include non-separable utilities, market incompleteness, learning, uncertainty, differences of opionions, ex-ante and ex-post asymmetric information, ambiguity and Knightian uncertainty. The second objective is to teach students how to think of asset pricing research under a bigger or richer framework. We shall focus on the interactions between asset pricing and other fields such as macroeconomics, corporate finance, financial institutions, and international finance. The goal of inventigating the joint dynamics is not only to better understand how asset prices are determined, but also (maybe more importantly) how would asset pricing dynamics affect other important economic vaiables such as investment, corporate payout and financing, unemployment, risk sharing, and international capital flows. Students will learn production-based asset pricing models, particularly the asset pricing models with investment-specific technology shocks, risk shocks, financial friction, searching frictions and information frictions. Of course, the advanced solution methods will focus too. The third objective is to introduce advanced empirical methods to analyze the data and the quantitative dynamic models. It includes how to estimate structural dynamic models, how evaluate structural models beyond goodness-of-fit tests, how confront the models predictions with empirical data by simulation and re-sampling techniques, and how to efficiently test models and explore new patterns using asset pricing and macro data.
“Competition Network: Distress Spillovers and Predictable Industry Returns”
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.…Read More
Knowledge at Wharton - 11/10/2023