Course description

Research Methodology in Finance


Welcome to this mandatory and important research methodology course in Finance. The importance of this course can be summarised in the following three questions:
1) What do I need in order to be able to identify the empirical predictions of a financial or economic theory?
2) What do I need in order to be able to test the empirical predictions of the theory?
3) What do I need in order to be able to critically evaluate the research methodology used in financial research?
Answer: Research Methodology in Finance.

Course content

This course introduces students to modern econometric techniques that are relevant for empirical research in Finance. The course starts with a session on data gathering in the library. Then univariate time series models and forecasting are covered before we move on to multivariate time series models and cointegration. The focus then switches to the modeling of volatility.

Course Content:

  1. Data gathering
  2. Review of the classical linear regression model
  3. Univariate time series analysis
  4. Multivariate time series analysis
  5. Cointegration: Modeling long-run financial behaviour
  6. Modelling Volatility: GARCH models
  7. Information search strategies and source evaluation

Each topic will be accompanied by hands-on practical applications of empirical Finance topics. 

During the semester there will be thesis seminars to guide the students towards writing a thesis registration form. This is conducted outside the course.

Learning outcome knowledge

The aim of this course is to introduce students to important econometric techniques that are used in empirical Finance and to facilitate an awareness in students of how these techniques can be applied. After completing this course, you should be able to employ and understand most of the research methodology used in today's published research in empirical Finance.

More specifically, you should:

  • have an advanced knowledge of the principles and methods of modern financial econometrics;
  • have extended and deepened your understanding of Econometrics gained in your basic Econometrics course and improved your critical judgement and discimination in the choice of techniques applicable to complex situations;
  • have extended your understanding of the application of econometric methods and interpretation of the results at an advanced level;
  • have further practiced problem solving skills at an advanced level and the use of econometric software.

Understanding of information search strategies:

  • acquaintance with methods for information "harvesting" and¬†search techniques;
  • know what a critical literature review is and how this type of articles may be searched for and used;
  • critical evaluation of sources.

Exam organisation

  • Written assignment: 20%
  • Written assignment: 20%
  • Written assignment: 10%
  • Written exam: 50%