Advanced Financial Empirical Research (AFER)

Course description



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.


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

Knowledge and understanding
After completing the courses, students shall demonstrate:
1. A deep understanding of the selected empirical issues in finance,
2. A thorough understanding of the important models and research methods in empirical finance.

Skills and abilities
Students shall have the ability to independently
3. Apply the models and methods they have learnt on new problems and to carry out their own empirical analyses,
4. Use scientific methods to analyse quantitative empirical material.

Judgement and approach
Students shall be able to independently
5. Search for relevant information from literature within finance,
6. Evaluate literature within finance.

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Course title:
Advanced Financial Empirical Research
Semester: Autumn term 2018
Study period: 3 4
Rate of studies: 50%
Level: Graduate level (second cycle)
Credits: 7.5
Language of instruction: English

Course code: FE5126

Syllabus

Contact:


Course coordinator:
Doris Rehnström
Head of course:
Lu Liu
Examiner:
Lu Liu
Student services:
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