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Advanced Financial Empirical Research

The goal of the course is to deepen students' understanding of models and research methods used in empirical finance research.

The course equips students with models and research methods used in empirical finance. The course aims to enhance students’ capability in understanding and assessing prior empirical research in finance, applying the models and methods they have learnt on new problems, and carrying out their own empirical analysis.
Methods to be introduced in the course include panel data models, limited dependent variable regressions, multifactor pricing models and volatility and correlation modeling.

The course will focus on the use of these methods for topics including empirical asset pricing, corporate default and credit rating, household financial decisions, and financial market policy effects. This course consists of lectures and several teacher-guided computer-based exercises. Being highly practical, this course prepares students for writing master thesis in finance.

  • Course structure

    Teaching format

    The course consists of a combination of lectures and computer labs and requires a significant portion of selfstudy on the part of students. Assessment for the course will be continuous and is carried throughout the different activities of the course.
    The course workload is 200 hours equivalent to 7,5 ECTS.
    The language of instruction is English. Please note that all teaching and learning activities - such as lectures, teacher-guided computer labs and assessment tasks – are carried out in English.


    Assessment for the course will be continuous and is carried throughout the different course activities. Each assessment task is weighted in relation to its importance in the overall assessment of the course. The student’s results from the different assessment tasks are added up to a total course score that will then translate into the final grade for the course.

    Assessment tasks

    The course contains the following weighted assessment tasks

    1. Individual final examination.
    2. Computer lab exercises.

    In order to obtain a passing grade a student be assessed on all intended learning outcomes and therefore participate in all assessment tasks.

    After completion of the course, students will receive grades on a scale related to the intended learning outcomes of the course. Passing grades are A, B, C, D and E. Failing grades are Fx and F. A grade Fx can be completed for a grade E.

  • Schedule

    The schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course.
  • Course literature

    Note that the course literature can be changed up to two months before the start of the course.

    See reading list in the current syllabus.

  • Course reports

  • Contact

    Course coordinator:
    Head of course: Lu Liu