Winston Dou

Winston (Wei) Dou's research focus lies at the intersection of finance, macroeconomics, and econometrics, in particular the impact of economic uncertainty, the role of market imperfection and incompleteness, the interactions of international asset prices and capital flows and their roles in understanding global imbalances, and new econometric methods for analyzing structural models. His articles have appeared in the Annals of Statistics and Journal of American Statistics Association. His research has received multiple academic awards.

One of his recent research projects quantitatively and empirically investigates how heightened economic uncertainty affects asset prices and investment. Intuitively speaking, economic uncertainty is the blurriness or randomness of firmspecific economic prospects. Interestingly, he finds that, in the model as in the data, uncertainty is not always fearfully evil as the economy has experienced around the late 2000s financial crisis; in fact, it can sometimes be welcomed and embraced by investors.

He joined Wharton in 2016 as an assistant professor of finance. Previously, he studied financial economics at MIT. He also received another doctoral degree in statistics from Yale University in 2010. He obtained a B.S. in mathematics and another B.S. in economics from Peking University in China.

Link to Personal Webpage of Research

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 nonseparable utilities, market incompleteness, learning, uncertainty, differences of opinions, exante and expost 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 productionbased asset pricing models, particularly the asset pricing models with investmentspecific 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 goodnessoffit tests, how to confront the models’ predictions with empirical data by simulation and resampling 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 fastgrowing 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 nonarbitrage principle and the law of one price to dynamic models through three different approaches: the binomial tree model, the BlackScholesMerton option pricing model, and the simulationbased 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 noarbitrage conditions do not hold.

Past Courses

FNCE206 FINANCIAL DERIVATIVES

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 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 portfolos, strategic corporate decisions, and stages in venture capital investing. The golobal derivatives market is one of the most fastgrowing markets, with over $600 trillion notional value in total. It is important as ever to understand both the strategic opportunities offered by these derivative instruments and 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 metholologies, we apply the nonarbitrage principle and the law of one price to dynamic models through three different approaches: the binomial tree model, the BlackScholesMerton option pricing model, and the simulationbased 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 disucssions, we also emphasize practical considerations of implementing strategies using derivatives as tools, especially when noarbitrage conditions do not hold.

FNCE717 FINANCIAL DERIVATIVES

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 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 portfolos, strategic corporate decisions, and stages in venture capital investing. The golobal derivatives market is one of the most fastgrowing markets, with over $600 trillion notional value in total. It is important as ever to understand both the strategic opportunities offered by these derivative instruments and 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 metholologies, we apply the nonarbitrage principle and the law of one price to dynamic models through three different approaches: the binomial tree model, the BlackScholesMerton option pricing model, and the simulationbased 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 disucssions, we also emphasize practical considerations of implementing strategies using derivatives as tools, especially when noarbitrage conditions do not hold.

FNCE934 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 nonseparable utilities, market incompleteness, learning, uncertainty, differences of opionions, exante and expost 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 productionbased asset pricing models, particularly the asset pricing models with investmentspecific 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 goodnessoffit tests, how confront the models predictions with empirical data by simulation and resampling techniques, and how to efficiently test models and explore new patterns using asset pricing and macro data.