2024/2025 KAN-CEADO2004U Financial Econometrics
English Title | |
Financial Econometrics |
Course information |
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Language | English |
Course ECTS | 7.5 ECTS |
Type | Mandatory (also offered as elective) |
Level | Full Degree Master |
Duration | One Semester |
Start time of the course | Spring |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Max. participants | 50 |
Study board |
Study Board for OECON and ECFI
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Course coordinator | |
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Main academic disciplines | |
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Teaching methods | |
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Last updated on 16-01-2024 |
Relevant links |
Learning objectives | ||||||||||||||||||||||||||||||||||||||||||||||||||
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Course prerequisites | ||||||||||||||||||||||||||||||||||||||||||||||||||
This is a mandatory course for the MSc in
Advanced Economics and Finance. It is assumed that students have
knowledge similar to the course KAN-COECO1058U Econometrics .
The course has 60 contact hours and there is a high level of interaction between lecturer and students, and in general a high work load. To sign up send a 1-page motivational letter, a 1-page CV, and a grade transcript to ily.stu@cbs.dk before the registration deadline for elective courses. You may find the registration deadlines on my.cbs.dk ( https://studentcbs.sharepoint.com/graduate/pages/registration-for-electives.aspx ). Please also remember to sign up through the online registration. |
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Examination | ||||||||||||||||||||||||||||||||||||||||||||||||||
The exam in the subject consists of two parts:
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Course content, structure and pedagogical approach | ||||||||||||||||||||||||||||||||||||||||||||||||||
The aim of the course is to provide the students with an understanding of models and estimation methods within the field of time series econometrics. The course will provide both a theoretical and an applied (hands on) angle on the topic. Practical aspects will be discussed and statistical properties will be proved. Linear, nonlinear, conditional heteroskedasticity, and multivariate models will be considered. Applications in finance and macroeconomics will be discussed.
The course builds on a standard introductory course in econometrics. Knowledge of fundamental concepts of mathematics and statistics is required. The students need to be familiar with matrix notation. |
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Description of the teaching methods | ||||||||||||||||||||||||||||||||||||||||||||||||||
Lectures and computer based exercise classes.
Please bring a laptop to all classes and labs. |
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Feedback during the teaching period | ||||||||||||||||||||||||||||||||||||||||||||||||||
Feedback is provided in numerous ways throughout
the course:
During office hours, we can discuss particular problems and give advice on individual academic development questions. Especially students can receive feed-back individually on the thoughts they have concerning data and model choice for the final exam project. Furthermore, each student will have the possibility to receive 20 minutes of individual supervision for the final exam project. During classes, we will do various exercises and discussions of solutions. Exercises can be suggested both by the teacher and by the students. Students are also encouraged to bring data for analysis in class (however not the data they plan to use for their exam projects). Feed-back in class will be from teacher to the whole class and also peer-to-peer during sessions with group work on exercises. After the midterm exam it will be possible for a student to sign up for an office hours session to have an explanation of his/her grade. Furthermore, indicative solution and a possibility for a discussion in class is also available for the midterm. Feed-back on individual progress on the hand-on computing part of the course is available during the exercise classes for the full semester. The course is evaluated by the students and the teachers discuss the evaluations with the students in the last class. Finally, the teacher makes sure that discussion fora in CANVAS allow students to ask questions for all parts of the syllabus and in relation to the exams . Here feed-back is typically visible for the whole class. Also individual more anonympus feed-back can be obtained by asking questions directly to the teacher by e-mail. |
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Student workload | ||||||||||||||||||||||||||||||||||||||||||||||||||
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Further Information | ||||||||||||||||||||||||||||||||||||||||||||||||||
Part of this course may also be taken as a PhD course for a limited number of PhD students. |
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Expected literature | ||||||||||||||||||||||||||||||||||||||||||||||||||
Indicative:
Enders, W. (2015): Applied Econometric Time series, 4th edition, Wiley
Tsay, R.S. (2010): Analysis of Financial Time series, 3rd edition, Wiley
Shumway, R. H and D. S. Stoffer (2017). Time Series Analysis and Its Applications: With R Examples, Springer.
Linton, O. (2019). Financial Econometrics: Models and Methods, Cambridge University Press.
Please also check CANVAS before course start. |