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| Semester | Herbstsemester 2020 |
| Angebotsmuster | Jedes Herbstsemester |
| Dozierende | Tim Kröncke (t.kroencke@unibas.ch, BeurteilerIn) |
| Inhalt | This course covers important and controversial topics in empirical finance. First, we will survey empirical facts and then implement tests of theories to understand the facts. We will cover topics in asset pricing as well as corporate finance. More specifically, we will study the time-series properties of the aggregate stock market and cross-sectional behaviour of individual stocks; how to implement an event study to measure the effect of an economic event on the broad market or the value of a company. |
| Lernziele | Lectures are 90 minutes followed by a computer-lab session of 90-120 minutes. In the computer lab session, you will learn step by step how to implement workhorse methods in finance using Matlab. We will work with measures of the aggregate stock market as well as a large dataset of individual firms (CRSP/COMPUSTAT). The focus is on the stock market, however, topics related to bond markets and FX markets may be covered as well (if time permits). |
| Literatur | See Syllabus (available on ADAM; send an e-mail to t.kroencke@unibas.ch to get access to ADAM) |
| Weblink | Weblink |
| Teilnahmebedingungen | Prerequisites: I assume that you have completed successfully the core modules in particular Econometrics (12036) and Advanced Macroeconomics and Finance (40105). We will spend a lot of time using the software Matlab. Prior work experience with Matlab is helpful, but not mandatory. (The first two days of the course provide an introduction to Matlab.) We will take a hands-on approach and will apply theories and empirical methods to the data. Depending on your learning preferences, you may want to have a better understanding of the theories and methods before looking on the data. The following courses cover the theories and methods in more detail: Intermediate Finance (10634), Advanced Asset Pricing (10600), Unternehmerisches Finanzmanagement (20391), Advanced Financial Accounting (30676), Time Series Analysis I (10684), Computational Economics (23525), Applied Financial Data Management (19799). |
| Anmeldung zur Lehrveranstaltung | Please register for the course and the subsequent exam by sending an e-mail (with your matriculation number) to the professor (t.kroencke@unibas.ch). The application deadline is August 3, 2020! The application is binding. In case of non-participation after registration it will be noted as "nicht erschienen" in the transcript. Your course registration can be seen in MOnA after the registration period is over. |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| Intervall | Wochentag | Zeit | Raum |
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Keine Einzeltermine verfügbar, bitte informieren Sie sich direkt bei den Dozierenden.
| Module |
Modul: Ausgewählte Themen aus Ökonomie und Rechtswissenschaft (Masterstudium: Actuarial Science) Vertiefungsmodul: Finance, Controlling and Banking (Masterstudium: Wirtschaftswissenschaften) Vertiefungsmodul: Monetary Economics and Financial Markets (Masterstudium: Wirtschaftswissenschaften) |
| Leistungsüberprüfung | Semesterendprüfung |
| Hinweise zur Leistungsüberprüfung | 6 CP. Grading is based on a final written exam at the end of the semester (50%), and up to four assignments during the semester (50%). Physical attendance is recommended. However, the course can be also studied remotely (the required material will be available on ADAM) and will be accompanied by video conferences for Q&As Date of the written exam: 19.10.20; 16:15-18:00. You will receive the room and place list by email. The exam will take place after October 12, 2020. |
| An-/Abmeldung zur Leistungsüberprüfung | An- und Abmelden: Dozierende |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | 1-6 0,1 |
| Wiederholtes Belegen | beliebig wiederholbar |
| Zuständige Fakultät | Wirtschaftswissenschaftliche Fakultät / WWZ, studiendekanat-wwz@unibas.ch |
| Anbietende Organisationseinheit | Wirtschaftswissenschaftliche Fakultät / WWZ |