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040045 KU Econometrics in Finance (MA) (2021W)
Continuous assessment of course work
Labels
ON-SITE
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 13.09.2021 09:00 to Th 23.09.2021 12:00
- Registration is open from Mo 27.09.2021 09:00 to We 29.09.2021 12:00
- Deregistration possible until Fr 15.10.2021 23:59
Details
max. 50 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 05.10. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
- Tuesday 05.10. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 07.10. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Tuesday 12.10. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
- Tuesday 12.10. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 14.10. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Tuesday 19.10. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
- Tuesday 19.10. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 21.10. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 28.10. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 04.11. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Tuesday 09.11. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
- Tuesday 09.11. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 11.11. 12:30 - 14:00 Seminarraum 17, Kolingasse 14-16, OG02
- Tuesday 16.11. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
- Tuesday 16.11. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 18.11. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Tuesday 23.11. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
- Tuesday 23.11. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 25.11. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Tuesday 30.11. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
- Tuesday 30.11. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 02.12. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Tuesday 07.12. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
- Tuesday 07.12. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 09.12. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Tuesday 14.12. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
- Tuesday 14.12. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 16.12. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Tuesday 11.01. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
- Tuesday 11.01. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 13.01. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Tuesday 18.01. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
- Tuesday 18.01. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 20.01. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Tuesday 25.01. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
- Tuesday 25.01. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
- Thursday 27.01. 13:15 - 14:45 Seminarraum 17, Kolingasse 14-16, OG02
Information
Aims, contents and method of the course
Assessment and permitted materials
The assessment consists of the following parts:i) Homework assignments. Students will receive several homework assignments during the semester, which have to be solved within a week, have to be uploaded via Moodle and have to be presented in the tutorials. The assignments can consist of small questions, analytical derivations and/or small data work in R.ii) Empirical projects. After each major section or chapter in class, one or several topics for an empirical project based on material covered in the course will be announced. Students can choose a topic on a first-come-first-served basis and have to work on it in a take-home project. In these projects, students will receive datasets (or have to find datasets) and have to perform econometric analyses in R in order to address certain economic questions. The analysis and results have to be documented in a slide presentation. The presentation (ca. 30 min.) has to be given approximately two weeks after the topic has been chosen either in class or in the tutorial. All underlying material (i.e., slides and all R codes used) have to be uploaded via Moodle prior to the presentation. Each student has to give one presentation per semester. Depending on the number of students in class, group work might be allowed (will be announced in due time).(iii) Oral exam on all material covered in the course. Depending on the number of students it will take place individually or in groups (will be announced in due time). The oral exams will take place during February 2022 and will be announced in due time.Permitted material: For assignments (i) and (ii), any material can be used. In the oral exam, no material is permitted.
Minimum requirements and assessment criteria
Grading:
For the final grade, (i) counts 35%, (ii) counts 30%, and (iii) counts 35%.To pass the course, a minimum level of 45% has to be reached.Rating:
[85%; 100%]: 1.0
[70%; 85%): 2.0
[55%; 70%): 3.0
[45%; 55%): 4.0
[0; 45%): 5.0
For the final grade, (i) counts 35%, (ii) counts 30%, and (iii) counts 35%.To pass the course, a minimum level of 45% has to be reached.Rating:
[85%; 100%]: 1.0
[70%; 85%): 2.0
[55%; 70%): 3.0
[45%; 55%): 4.0
[0; 45%): 5.0
Examination topics
All material covered in class and in the tutorials.
Reading list
Brooks, C. (2008): “Introductory Econometrics of Finance”, 2nd ed., Cambridge University Press
Campbell, J. Y., A. W. Lo, and A. C. MacKinlay (1997): ''The Econometrics of Financial Markets'', Princeton University Press
Hamilton, J. D. (1994): ''Time Series Analysis'', Princeton University Press
Hautsch, N. (2012): “Econometrics of Financial High-Frequency Data”, Springer.
Taylor, S. J. (2005): ''Asset Price Dynamics, Volatility, and Prediction'', Princeton University Press
Tsay, R. S. (2010): ''Analysis of Financial Time Series: Financial Econometrics'', Wiley, 3rd edition
Campbell, J. Y., A. W. Lo, and A. C. MacKinlay (1997): ''The Econometrics of Financial Markets'', Princeton University Press
Hamilton, J. D. (1994): ''Time Series Analysis'', Princeton University Press
Hautsch, N. (2012): “Econometrics of Financial High-Frequency Data”, Springer.
Taylor, S. J. (2005): ''Asset Price Dynamics, Volatility, and Prediction'', Princeton University Press
Tsay, R. S. (2010): ''Analysis of Financial Time Series: Financial Econometrics'', Wiley, 3rd edition
Association in the course directory
Last modified: Mo 08.11.2021 09:48
This course aims to provide students an introduction into the field and an overview of the most important topics and techniques. Having predominantly an applied focus, it attempts to balance between derivations of basic theoretical relations, fundamental methodology, the analysis of specific financial econometric models, applications thereof as well as the discussion of important empirical findings.
The course deals with the estimation and testing of asset pricing models, univariate and multiple time series techniques to model and to predict financial data as well as the modelling of time-varying volatility and risk. Current topics in modern financial econometric research, such as the modelling of realized volatility as well as the analysis of financial high-frequency data, among others, is covered as well.
Moreover, an important objective is to provide a comprehensive knowledge to do empirical work in financial research and practice. Therefore, a part of the course consists of practical exercises where students are instructed to apply econometric concepts to real financial data. In this context, students will be introduced to basic programming and application steps using the statistical software package R.