Veranstaltungen im Wintersemester 2023/2024

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).

 

Veranstaltungen im Sommersemester 2023

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

 

Veranstaltungen im Wintersemester 22/23

Vorlesung "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.

 

 

Veranstaltungen im Sommersemester 2022

Seminar "Machine Learning Stock Returns with Option Data"

Eine zentrale Fragestellung im Asset Pricing ist die Vorhersagbarkeit von Aktienrenditen. Werden Variablen identifiziert, die es ermöglichen Aktienrenditen vorherzusagen, stellt dies aber nicht zwangsläufig eine Arbitragemöglichkeit dar. Es kann sich dabei auch um eine Kompensation in Form einer Risikoprämie für riskantere Investitionen handeln. Ziel des Seminars ist es zu analysieren, inwiefern verschiedene Machine Learning Methoden unter Verwendung von Optionsdaten dazu beitragen, die Aktienrenditen im Querschnitt besser zu erklären.

Weitere Details inklusive den Themenbeschreibungen gibt es in Kürze auf unserer Homepage und im WiWi-Portal.

Termine:

- Bewerbungsfristen: 01.04.2022

- Blockseminar: 14./15.07.2022

 

Vorlesung "Asset Pricing" 

Die Vorlesung Asset Pricing beschäftigt sich mit der Bewertung von risikobehafteten Zahlungsansprüchen. Dabei müssen die Zeitstruktur und die Unsicherheit der Zahlung berücksichtigt werden. Die Vorlesung führt einen stochastischen Diskontierungsfaktor sowie eine zentrale Bewertungsgleichung ein, die zur Bewertung beliebiger Zahlungsansprüche verwendet werden kann. Dies gilt sowohl für Aktien als auch für Anleihen oder Derivate. Der erste Teil der Vorlesung stellt den theoretischen Rahmen vor, der zweite Teil befasst sich mit empirischen Fragen der Bewertung von Vermögenswerten.

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

 

Vorlesung "Derivate"

Die Veranstaltung Derivate beschäftigt sich mit den Einsatzmöglichkeiten und Bewertungsproblemen von derivativen Finanzinstrumenten. Nach einer Übersicht über die wichtigsten Derivate und deren Bedeutung werden zunächst Forwards und Futures analysiert. Daran schließt sich eine Einführung in die Optionspreistheorie an. Der Schwerpunkt liegt auf der Bewertung von Optionen in zeitdiskreten und zeitstetigen Modellen. Schließlich werden Konstruktions- und Einsatzmöglichkeiten von Derivaten etwas im Rahmen des Risikomanagements diskutiert.

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