Simon Business School

Course Offerings

The Course Catalog (formerly known as the Information Guide) contains degree requirements and course descriptions.

 

PHD FINANCE COURSES

 

FIN 505. THEORY OF FINANCE

The goal of this course is to present the theory of asset pricing and portfolio selection in multi-period settings under uncertainty. The asset pricing results are based on three increasingly restrictive assumptions: single-agent optimality, absence of arbitrage and equilibrium. These results are unified with two key concepts: pricing kernels and martingales. The course draws connections between these concepts and makes plain the similarities between discrete and continuous time models. Applications include term structure models, portfolio choices and the pricing of corporate securities.

This course will follow the semester schedule.

FIN 511. CONTINUOUS TIME THEORY IN FINANCE

The course builds on the basic theory presented in FIN 505 Theory of Finance. FIN 511 will emphasize some relatively advanced mathematical methods that are used in the research literature of financial economics. The objective of the course is to provide the student with enough knowledge of these methods that he or she can begin to use them in nontrivial ways in his or her research. Particular emphasis is given to topics that are costly or difficult to learn on an individual basis.

The methods surveyed in the course are primarily techniques for constructing and analyzing continuous-time models of trading and of stochastic asset price behavior. Virtually all of the derivative security pricing models and many of the multifactor models of asset prices and the term structure of interest rates are of this type.

FIN 512. EMPIRICAL ASSET PRICING

This course covers classic contributions and recent developments in capital markets research, both applied theoretical and empirical, in relation to corporate policies, business cycle and economic growth. Specific topics include time-series predictability of stock market returns, empirical methods and evidence on the cross-section of returns, evidence on mutual fund performance and the closed-end fund puzzle, event studies and the empirical relations between stock returns and  corporate policies, consumption-based asset pricing, applied equilibrium modeling of asset pricing anomalies and behavioral finance.

FIN 513. AGENCY THEORY

The course studies game theoretic foundations of the theory of the firm. The strong emphasis is placed on corporate finance. The topics include capital structure, asymmetric information and signaling, contract design, and optimal security design. In addition, we look into information aggregation in financial markets, bargaining with asymmetric information, and dynamic signaling – important and fascinating topics in the broader area of information economics.

FIN 514. EMPIRICAL CORPORATE

This course covers cross-sectional and panel data empirical methods used in corporate finance research. The course will expose students to a variety of methods commonly employed in empirical research. While the course will cover the efficiency and consistency of various estimators, the primary focus will be on how econometric tools can be used to identify unbiased causal effects. Lectures and econometric readings will provide students with econometric intuition behind each method covered in the course. Course readings will expose students to examples of the methods being used in published and working papers. Assignments will familiarize students with standard datasets used in corporate finance and will enable students to apply the methods covered in the course and to analyze and criticize other researchers’ use of common empirical methods.

FIN 523. ADVANCED AGENCY THEORY

The course studies dynamic aspects of the theory of the firm. The strong emphasis is placed on the role of time and repeated decisions in firm management. The topics include real options, dynamic lemons markets, dynamic contracts, and investment under constraints. The course is research intensive, requiring completion of several referee reports and a term project.

FIN 524.  FINANCIAL AND ECONOMIC NETWORKS

Networks have experienced a tremendeous growth in the past years in many areas of finance and economics. The course teaches tools and methodologies needed for performing cutting edge empirical and theoretical research that relies on modeling and analysing networks of economic agents (individuals, banks, firms, countries). The topics include over-the-counter financial markets, production networks, payment networks and more. The applications will cover all three areas of finance: asset pricing, corporate finance and financial intermediation. The course is research intensive, requiring completion of several referee reports and a term project.  

 

AEC 510. PHD WORKSHOP IN APPLIED ECONOMICS

The workshop provides a forum for the presentation of ongoing and completed research projects by PhD students in the economics core. Third- and fourth-year PhD students are expected to participate actively.

Prerequisite: permission of the instructor

 

ADDITIONAL REQUIRED ECONOMICS COURSES

 

ECO 471.  MODERN VALUE THEORY 1

The foundation of modern microeconomic analysis, including consideration of consumer behavior, the theory of the firm, equilibrium under alternative market structures, and welfare implications.

ECO 472.  MODERN VALUE THEORY

Introduction to non-cooperative game theory, asymmetric information models, and social choice theory.

ECO 483/484.  INTRODUCTION TO MATH STATISTICS/INTRODUCTION TO ECONOMETRICS

Elements of probability theory and statistics, as employed in the econometrics sequence.   Estimation and hypothesis testing in the standard linear model; linear restrictions, dummy variables, multicollinearity, weighted least squares and specification error.

ECO 485.  INTRODUCTION OF ECONOMETRICS

Extensions of the general linear model to handle serial correlation, heteroskedasticity, simultaneity.  Maximum likelihood estimation and testing.  Diagnostic checking of estimated models.  Problems in the analysis of individual unit data-qualitative dependent vriables and sample self-selectivity.

 
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