Courses in winter semester 22/23

Lecture "Advanced Empirical Asset Pricing"

In this course we will discuss the fundamentals of Asset Pricing and how to test them. Although this is an Empirical Asset Pricing course, we deal with some concepts from Asset Pricing Theory that we can test afterwards (CAPM, ICAPM, CCAPM, recursive utility). Besides, the course will cover the most important empirical methods to do so. For that purpose, we will discuss the overarching tool Generalized Method of Moments, and the special cases of OLS and FMB regressions. Every second week, we will meet for a programing session, in which we will look at the data to draw our own conclusions. An introduction to the software MATLAB will be given at the beginning of the course. Students should bring a laptop to these sessions. Programing skills are not required but helpful.

We start with a review of the Stochastic Discount Factor, which is already known from the course „Asset Pricing“. We then derive the CAPM and the Consumption-CAPM as special cases from the general consumption-savings optimization problem of the rational investor. In the first part of the course we discuss the CAPM and, as natural extensions, models with multiple factors. Prominent phenomena such as the value premium and momentum are discussed. In the second part of the lecture we will study extensions of the Consumption-CAPM and study the implications of exotic preferences.

Organizational details: The course takes place in the first half of the semester (between October and early December). Lectures will be provided as videos on ILIAS. In addition, we will meet twice per week. These meetings can be attended on-campus (for healthy students only) or online via zoom. On Mondays (9:45 a.m.), we will discuss questions the students have while watching the videos (flipped classroom style). On Tuesdays (9:45 a.m.), we will be programming during the meetings. The syllabus with an exact schedule will be provided on ILIAS in due time.




Courses in summer semester 2022

Seminar "Machine Learning Stock Returns with Option Data"

A central issue in asset pricing is the predictability of stock returns. If variables are identified that make it possible to predict stock returns, it does not necessarily represent an arbitrage opportunity. It can also be a compensation in the form of a risk premium for riskier investments. The aim of the seminar is to analyze to what extent different machine learning methods using option data contribute in better explaining cross-sectional stock returns.

Further details including the specific topics will be available soon on our homepage and on the WiWi portal.


- Application Deadline: 01. April 2022

- Block seminar: 14./15. July 2022


Lecture "Asset Pricing" 

The lecture Asset Pricing deals with the valuation of risky payment claims. The time structure and the uncertain amount of the payment must be taken into account. The lecture introduces a stochastic discount factor as well as a central valuation equation which can be used to evaluate any kind of payment claims. This includes shares as well as bonds or derivatives. The first part of the lecture presents the theoretical framework, the second part deals with empirical questions of asset pricing.

Basic literature:  Cochrane, J. (2005). Asset pricing - Rev. ed., Princeton Univ. Press.


Lecture "Derivate" (Derivatives)

The lecture Derivatives deals with the possible applications and valuation problems of derivative financial instruments. After an overview of the most important derivatives and their significance, first of all forwards and futures are analyzed. This is followed by an introduction to option pricing theory. The focus is on the valuation of options in discrete-time and continuous-time models. Finally, construction and application possibilities of derivatives are discussed, for example in the context of risk management.

Basic literature: Hull, J. (2012) Options, Futures, & Other Derivatives, Prentice Hall, 8th Edition.