Universität Wien FIND

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040187 KU Financial Markets and Information (MA) (2021S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Prüfungsimmanente Lehrveranstaltung
DIGITAL
Do 20.05. 13:15-14:45 Digital

An/Abmeldung

Details

max. 50 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

The course starts digitally on Thursday, 4 March 2021 at 1.15 pm.
Final Exam: Wednesday, 30th of June, 13.15 - 14.45

Donnerstag 04.03. 13:15 - 14:45 Digital
Donnerstag 11.03. 13:15 - 14:45 Digital
Donnerstag 18.03. 13:15 - 14:45 Digital
Donnerstag 25.03. 13:15 - 14:45 Digital
Donnerstag 15.04. 13:15 - 14:45 Digital
Donnerstag 22.04. 13:15 - 14:45 Digital
Donnerstag 29.04. 13:15 - 14:45 Digital
Donnerstag 06.05. 13:15 - 14:45 Digital
Donnerstag 27.05. 13:15 - 14:45 Digital
Mittwoch 02.06. 13:15 - 14:45 Digital
Donnerstag 10.06. 13:15 - 14:45 Digital
Donnerstag 17.06. 13:15 - 14:45 Digital
Donnerstag 24.06. 13:15 - 14:45 Digital
Mittwoch 30.06. 13:15 - 14:45 Digital

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

In the course ‘Financial Markets and Information’ we analyse the inclusion of information in prices, from an intuitive and theoretical perspective. In addition, we are going to test how our intuition matches with our observation of real financial markets.
The course splits up in four different parts. In the first part we introduce the optimal learning and information updating when receiving signals. First, we cover Bayes’ rule and continue with filtering information about a fundamental out of signals we observe. We study the Kalman filter as an optimal linear filter.
In the second part, we consider, how information gets included and is reflected in prices. In this part, we study competitive models in which individual traders do not move prices. In this context, the rational expectations equilibrium (fully revealing, partially revealing, noisy information) plays a key role. We will also cover costly information acquisition and the Grossman-Stiglitz paradox. Herding and social learning conclude this part.
The third part covers strategic market models, in which one informed agent’s information can change prices. We investigate the relationship between price impact and the market mechanism design. The timing of information, the number of informed traders and market clearing mechanisms are important factors to consider.
In the fourth part, we cover behavioral information processing. As individuals tend to follow heuristics or make mistakes in their information processing, we examine well documented shortcomings in individual information processing and their impact on financial markets. Overconfidence and learning from experience will play a key role in our study of behavioral learning.

Art der Leistungskontrolle und erlaubte Hilfsmittel

The evaluation in this course will be based on four components:
The first component is a group presentation. In each week, starting week 3, a group of students presents the solution to a specified problem on the problem set at the beginning of the lecture.
The second component is a participation-based grade. The hand-in of a problem set is required for at least 8 weeks in the semester (out of 10 possible dates). When the problem set scores half of the possible points and minimum standards of lecture participation are met, full points are assigned.
The third and fourth components are a midterm exam in the eighth session and a final exam at the end of the course.

Mindestanforderungen und Beurteilungsmaßstab

7% Group Presentation

8% Problem Set Hand-in

40% Mid-term Exam

45% Final Exam

Prüfungsstoff

The midterm exam covers weeks 1-6 and the final exam covers all course content, with a focus on the course content not covered in the midterm.

Literatur

Vives, Xavier. Information and Learning in Markets: The Impact of Market Microstructure. Princeton University Press, 2010.

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mo 03.05.2021 11:07