Financial Econometrics and Quantitative Methods in Finance


Prerequisite/Recommended prerequisite for participation in the module

The module builds on knowledge obtained by the modules Analysis 2 and Probability Theory from the BSc in Mathematics-Economics.

Content, progress and pedagogy of the module

Learning objectives


  • understanding of the most common applied quantitative and empirical methods in econometrics, including in particular financial econometrics
  • knowledge about option pricing and estimation of time-varying volatility models
  • know about zero coupon term structure models
  • know about dynamic term structure models
  • know about models for stock portfolios and intertemporal asset pricing models
  • know about event studies in corporate finance
  • know about computational finance and Monte Carlo methods applied, e.g., to the pricing of exotic options


  • are able to argue for the importance of econometric/statistical methods in the analysis of a given financial problem
  • are able to build econometric models and judge their applicability


  • are able to demonstrate understanding of the theory of the econometric models and know how to reason within the models
  • are able to communicate the results of an econometric analysis to non-specialists in the financial sector
  • are able to analyse financial data using the available software

Extent and expected workload

This is a 5 ECTS course module and the work load is expected to be 150 hours for the student.



Name of examØkonometri og kvantitative metoder inden for finansiering
Type of exam
Written or oral exam
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentAs stated in the Joint Programme Regulations.


Facts about the module

Danish titleØkonometri og kvantitative metoder inden for finansiering
Module codeF-MOK-K1-4
Module typeCourse
Duration1 semester
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module


Study BoardStudy Board of Mathematics, Physics and Nanotechnology
DepartmentDepartment of Mathematical Sciences
FacultyFaculty of Engineering and Science