Lecture on "Advances Empirical Asset Pricing"

Purpose of the course

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. In most of the weeks 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.

Times and location

The course will be taught in flipped classroom style in the first half of the semester. The lectures are made available as videos on a weekly basis. The videos will be accompanied by questionnaires that should be filled out by the participants. Every week, the respective topics will be discussed in a corresponding Q&A session. These sessions take place on-site in room 209, building 09.21 (Blücherstr. 17). It is strongly recommended to watch the videos during the respective Q&A session.  In order to set the best possible meeting times for the course participants, we will hold a vote via the forum on ILIAS. Participation in this voting is possible until the end of the first week. The meeting times will then be announced on ILIAS.
We will also meet every week for programming sessions where we will implement the statistical methods discussed in the course. It is highly recommended to work on the programming tasks before the tutorial. We will also vote on the times for the tutorial via ILIAS and it is a good idea to schedule Q&A sessions and tutorials directly after each other.

Web resources

All the course materials (slides, videos, data, programs, syllabus, …) can be found on the ILIAS page of the course. Also all kinds of announcements related to the course will be posted exclusively on ILIAS.

Exercise Sessions

There will be problem sets, which will be discussed in the respective exercise sessions (see “Tentative Schedule” below). The idea of the exercise sessions is that we analyze the ideas/theories that we talk about in the lectures by looking at data. The first two exercise session will be a short introduction to the software MATLAB which will be used throughout the course. The problem sets and data will be made available for download on ILIAS one week before the exercise sessions, together with the respective videos. The idea is that you have enough time to work on the problems prior to the session.

Grading

The final grade for this course will be determined by the grade in the final exam. A bonus can be acquired through successful participation in the exercise sessions. If the grade of the final examination is between 4.0 and 1.3, the bonus improves the grade by one step (0.3 or 0.4). To get a bonus, students have to hand in their MATLAB code four times during the semester at least 30 minutes before the respective programming session (via mail: thimme ∂does-not-exist.kit edu).

Seminar "Big Data in Finance"

The prices of stocks aggregate all available information. But exactly what information is relevant to investors in their valuation is often unclear. Advances in data science have recently enabled financial market researchers to understand much better what information is relevant for asset prices. This seminar will discuss various recent works in this area. In addition, various results will be complemented by students' own analyses of a data set provided by the chair.

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

- Application deadline: 24 March 2023, 23:55

- Block seminar: 13./14. July 2023

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.

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.

Dates:

- 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.