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2021/2022  KAN-COECO1056U  Financial Econometrics

English Title
Financial Econometrics

Course information
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 MSc in Advanced Economics and Finance
Course coordinator
  • Lisbeth La Cour - Department of Economics (ECON)
Main academic disciplines
  • Finance
  • Statistics and quantitative methods
  • Economics
Teaching methods
  • Blended learning
Last updated on 18-06-2021

Relevant links
Learning objectives
  • Explain Time Series Econometric models for inference and predictions within macroeconomic and financial applications
  • Interpret and analyze estimation output within a Time Series framework.
  • Relate Time Series Econometric Code and output in econometric packages
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.
Examination
The exam in the subject consists of two parts:
Financial Econometrics - midterm:
Sub exam weight50%
Examination formWritten sit-in exam on CBS' computers
Individual or group examIndividual exam
Assignment typeWritten assignment
Duration2 hours
Grading scale7-point grading scale
Examiner(s)One internal examiner
Exam periodSpring
AidsLimited aids, see the list below:
The student is allowed to bring
  • Non-programmable, financial calculators: HP10bll+ or Texas BA II Plus
  • Language dictionaries in paper format
The student will have access to
  • Advanced IT application package
Make-up exam/re-exam
Same examination form as the ordinary exam
If the number of registered candidates for the make-up examination/re-take examination warrants that it may most appropriately be held as an oral examination, the programme office will inform the students that the make-up examination/re-take examination will be held as an oral examination instead.
Description of the exam procedure

All the learning objectives are relevant for this partial exam. However, for the midterm only the models mentioned by the teacher on CANVAS are part of the syllabus.

 

 

Financial Econometrics - final:
Sub exam weight50%
Examination formHome assignment - written product
Individual or group examIndividual exam
Size of written productMax. 10 pages
Assignment typeProject
DurationWritten product to be submitted on specified date and time.
Grading scale7-point grading scale
Examiner(s)One internal examiner
Exam periodSummer
Make-up exam/re-exam
Same examination form as the ordinary exam
Description of the exam procedure

The project will consist of an empirical paper based on data that is selected by each students. The empirical analysis must demonstrate that the student can choose relevant models and use them to estimate, interpret and possibly forecast (or use the models in other relevant ways) on their chosen data. Fulfilling the other learning objectives of the course will also be important. The student will be asked to use the statistical software offered for the course for their analysis. Each student will have the possibility to receive 20 minutes of individual supervision for the final exam project. Students are allowed to choose their data from the beginning of the course.

 

All the learning objectives are relevant for this partial exam.
Course content, structure and pedagogical approach

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.
Description of the teaching methods
Lectures and computer based exercise classes.

Please bring a laptop to all classes and labs.
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 a detailed 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.
Student workload
Lectures/Exercise classes 60 hours
Exam 6 hours
Preparation 140 hours
Further Information

Part of this course may also be taken as a PhD course for a limited number of PhD students.
Expected literature

Indicative:

 

Please see CANVAS before course start.
Last updated on 18-06-2021