2016/2017 KAN-COECO1056U Financial Econometrics
English Title | |
Financial Econometrics |
Course information |
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Language | English |
Course ECTS | 7.5 ECTS |
Type | Mandatory 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 |
Study board |
Study Board for MSc in Advanced Economics and
Finance
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Course coordinator | |
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Contact information: https://e-campus.dk/studium/kontakt | |
Main academic disciplines | |
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Last updated on 23-02-2017 |
Learning objectives | ||||||||||||||||||||||||||||||||||||||||||||||||
To achieve the grade 12, students should meet the
following learning objectives with no or only minor mistakes or
errors:
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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 one-page motivational letter, a one-page CV, and a grade transcript to oecon.eco@cbs.dk no later than 12 December 2016. 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 and structure | ||||||||||||||||||||||||||||||||||||||||||||||||
The aim of the course is to provide the students with an understanding of models, 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, conditional heteroskedasticity, and multivariate models will be considered. 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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Teaching methods | ||||||||||||||||||||||||||||||||||||||||||||||||
Lectures and computer based exercise classes.
Approximately 2.5 hours of lecture/week and 2.5 hours of lab/week. We'll most likely mix lectures and lab, so please bring a laptop to all classes and labs. The class will be taught with an R bent. |
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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: Main textbook:
For introductory material, see the undergraduate textbooks by Stock and Watson or Wooldrigde. |