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Syllabus

EN IT

Learning Objectives

The central theme of asset pricing is the valuations of uncertain future payoffs. In this introductory class, we cover the foundations of the theory in a static setup, and some important results in a continuous-time setting.

By the end of this course, you will:
◦ Understand key concepts in asset pricing.
◦ Communicate the intuition that underlies the Black and Scholes formula.
◦ Simulate models of asset prices and use numerical methods to price and hedge derivative securities.

Prerequisites

None

Program

The field of asset pricing aims to explain why financial assets have the returns they do. While we still do not have definite answers, the field developed thus far is insightful. This course covers some of the field’s milestones.

Our starting point is the assumption of competitive markets. We abstract away all frictions and build models that focus on risk. The rationale is that risk is the most critical factor in determining expected returns. Despite the elegance of the models, they fail to explain the data. Dividends (or consumption) are dramatically less volatile than stock prices, implying that the only way the models can match the data is if we assume investors have unreasonably high levels of risk aversion. We will discuss some extensions that attempt to bridge the gap between the data and the theory.

We then take a step backward and abstract from risk as well. We want to see how far we can go if we only require that investors prefer more to less. This so-called no-arbitrage theory will allow us to price derivative securities. Again, we will visit the data and see how well the classic no-arbitrage models perform.

Next, we will visit a purely statistical approach to asset pricing, the so-called Fama-French factors. Next, we look at some basic extensions of the theory that take into account investors’ psychology (so-called behavioral finance), asymmetric information (so-called wisdom of the crowd), and bubbles (this setup will also help us understand how fiat money, in a rational environment, can emerge as a feasible storage of value). To conclude the course, we learn how assets are priced in actual stock exchanges (so-called price discovery). With the help of a simple model that considers the price discovery process, we will gain insight into the real-world stock trading environment.

Books

We do not have a required textbook. We will read some classic academic papers that I’ll distribute. Several assignments will require programming. You can use any programming language you prefer.

Bibliography

None

Teaching methods

I will use the traditional lecture format and often develop the theory on the board. We will have, however, interactive activities in class. Therefore, students are expected to attend classes, keep up with required readings, and submit assignments in a timely manner. Assignments are an important part of the learning process in this course because they allow students to build their skills. Students can seek help from classmates when working on the programming assignments but must submit their own work.

Exam Rules

The final grade is based on
Homework (50%)
Final Exam (50%)

All assignments should be submitted through Teams. The final exam is an in-class written exam. Accordingly, students who withdraw or fail an exam may not take the exam again in the same exam session.