Winston Wei Dou

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.
• All Research from Winston Wei Dou »

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.

Current Courses

• FNCE2170 - Financial Derivatives

  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 )

• FNCE9110 - Financial Economics

  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 )

Past Courses

• FNCE2170 - Financial Derivatives

  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.

• FNCE3990 - Independent Study

  Integrates the work of the various courses and familiarizes the student with the tools and techniques of research.

• FNCE7170 - Financial Derivatives

  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.

• FNCE8990 - Independent Study

  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.

• FNCE9110 - Financial Economics

  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.

• FNCE9340 - Empirical Meth in Asset

  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.

• Golub Faculty Scholar Award at the Wharton School, 2024
• Best Paper Award, China FinTech Research Conference, 2024
• Wharton Dean’s Research Fund Award, 2024
• IRF Best Paper Award, Asian Finance Association, 2024
• Jacob Gold & Associates Best Paper Prize, ASU Sonoran Winter Conference, 2024
• Best Paper Award, ABFER-JFDS Conference on AI and FinTech, 2024
• Best Discussant Award, LBS Summer Finance Symposium, 2024
• Wharton Teaching Excellence Award at University of Pennsylvania, 2023
• Best Paper Award, Melbourne Asset Pricing Meeting, 2023
• Golub Faculty Scholar Award at the Wharton School, 2023
• Richard A. Crowell Memorial Prize, Second Prize, PanAgora Asset Management, 2022 Description

  “Competition Network: Distress Spillovers and Predictable Industry Returns”

• CFA Institute Asia-Pacific Research Exchange Award (NZFM), 2021
• Jacobs Levy Center Outstanding Research Paper Prize, 2021
• Semi-finalist of FMA Conference Best Paper Award, 2021
• Wharton Dean’s Research Fund Award, 2021
• PwC Finance Forum Best Paper Award, 2021
• NASDAQ Award for the Best Paper on Asset Pricing, Western Finance Association, 2020
• Best Paper Award on Asset Pricing, Northern Finance Association, 2020
• AAII Award for the Best Paper on Investments, Midwest Finance Association, 2020
• Best Paper Award, China International Conference in Macroeconomics (CICM), 2019
• Wharton Teaching Excellence Award at University of Pennsylvania, 2017
• Marshall Blume Prize, Rodney L White Center for Financial Research at Wharton, 2017
• MFM Dissertation Award, Becker Friedman Institute for Economics at UChicago, 2016
• Best Paper Award, Red Rock Finance Conference, 2013
• I. R. Savage Award in Nonparametric Statistics, American Statistical Association, 2009

Knowledge @ Wharton

• Building Stronger Family Offices by Sharing Knowledge and Securing the Future, Knowledge @ Wharton - 11/21/2024
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• How Are Companies Really Using AI? A New Report Has Answers, Knowledge @ Wharton - 11/19/2024
• Impact vs. Time: A Leader’s Guide to Slow Productivity, Knowledge @ Wharton - 11/19/2024
• Kevin O’Leary Illustrates the Benefits of Tariffs for U.S. Businesses, Knowledge @ Wharton - 11/19/2024
• Boosting Donations Through Self-expressive Choices | Jonah Berger, Knowledge @ Wharton - 11/19/2024
• Why Are Hospitals So Expensive?, Knowledge @ Wharton - 11/18/2024
• New Phenomena in Behavioral and Social Investing, Knowledge @ Wharton - 11/18/2024
• Bigger Hospitals, Better Care? Wharton Research Finds Benefits Are Only at the Operational Level, Knowledge @ Wharton - 11/14/2024
• Linda Dow Cash, CEO, Two Chicks Cocktails, Knowledge @ Wharton - 11/14/2024