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# FIN 3618 Financial Econometrics

## FIN 3618 Financial Econometrics

Course code:
FIN 3618
Department:
Finance
Credits:
7.5
Course coordinator:
Isaiah Hull
Course name in Norwegian:
Financial Econometrics
Product category:
Bachelor
Portfolio:
Bachelor of Finance - Programme Courses
Semester:
2023 Autumn
Active status:
Active
Level of study:
Bachelor
Teaching language:
English
Course type:
One semester
Introduction

Financial Econometrics is designed to help students understand and apply statistical techniques to financial data. Students will gain valuable analytical and programming skills that will enhance their ability to conduct research and perform financial analysis in industry settings. The course will center on linear regression, which is the most commonly used statistical technique in finance. It will provide a strong foundation for anyone interested in pursuing a quantitative role in the financial sector.

Learning outcomes - Knowledge

During the course, students should develop knowledge about:

• Regression analysis, which is frequently used to analyze financial data.
• Statistical inference, which can be used to draw conclusions about populations using a sample of data.
• Common issues and practices with financial data.
Learning outcomes - Skills

Upon completion of the course, the students should be able to:

• Estimate regression models.
• Perform hypothesis tests on the parameter estimates of the regression model.
• Test the assumptions underlying the classical linear regression model.
• Extract data from databases (e.g WRDS) and implement econometric techniques in the R programming language.
General Competence

In the course, the focus will be on the assumptions underlying the different theories and methods covered. Hence, it is expected that students have a critical attitude towards the realism of these.

Course content

1. Review of the mathematical and statistical foundations of financial econometrics.

2. Overview of the collection, transformation, and interpretation of financial data.

3. The capital asset pricing model (CAPM), which will be used in econometric exercises throughout the course.

4. Linear regression and its extensions, which form the foundation of financial econometrics.

5. Diagnostic tests for problems in linear regression.

Teaching and learning activities

The course elements include lectures, in-class exercises, online exercises, a graded group assignment, and a final exam. During the lectures, we will introduce new econometric techniques and discuss their practical application in R. To strengthen the students' understanding of these concepts, they will have to submit a group assignment. This will involve downloading the data themselves from a database (e.g., WRDS), importing the data into R, implementing the econometric analyses in R, and summarizing the results in tables or graphs. Here, strong emphasis will be placed on the interpretations of the results from a statistical as well as from an economic point of view.

Software tools
R
Qualifications

Higher Education Entrance Qualification

### Disclaimer

Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Required prerequisite knowledge

MET 2910 Mathematics and MET 2920 Statistics or equivalent.

Exam categoryWeightInvigilationDurationSupport materialsGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
FIN 36182
ECTS
Internal examiner
Resit:
Examination every semester
40No 1 Semester(s)Group (1 - 4)Group Assignment. All exams must be passed to obtain a final grade in the course.
Exam category:
Submission
Form of assessment:
Structured test
Exam code:
FIN 36183
ECTS
Internal examiner
Resit:
Examination every semester
60Yes2 Hour(s)
• BI-approved exam calculator
• Simple calculator
• Bilingual dictionary
Individual (1 - 1)Final examination. All exams must be passed to obtain a final grade in the course.
Exams:
 Exam category: Submission Form of assessment: Written submission Weight: 40 Invigilation: No Grouping (size): Group (1-4) Support materials: Duration: 1 Semester(s) Comment: Group Assignment. All exams must be passed to obtain a final grade in the course. Exam code: FIN 36182 Grading scale: ECTS Resit: Examination every semester
 Exam category: Submission Form of assessment: Structured test Weight: 60 Invigilation: Yes Grouping (size): Individual (1-1) Support materials: BI-approved exam calculator Simple calculator Bilingual dictionary Duration: 2 Hour(s) Comment: Final examination. All exams must be passed to obtain a final grade in the course. Exam code: FIN 36183 Grading scale: ECTS Resit: Examination every semester
Type of Assessment:
Ordinary examination
All exams must be passed to get a grade in this course.
Total weight:
100
ActivityDurationComment
Teaching
30 Hour(s)
Prepare for teaching
75 Hour(s)
Group work / Assignments
30 Hour(s)
Student's own work with learning resources
50 Hour(s)
Digital resources
15 Hour(s)
Student’s own work with learning platform material