GRA 6547 Research Methodology in Finance
GRA 6547 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 resarch? Answer: Research Methodology in Finance.
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. You should after completing this course 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
You should have developed further the following key skills:
- Written communication
- Oral communication
- Ethical awareness in conducting research
- Teamwork
- Problem solving and analysis
- Using initiative
- Computer Literacy
In the course there will be focus on the assumptions underlying the different theories and methods covered. Hence, it is expected that students will have a critical attitude towards the realism of these. The students should upon completion of the course have a good understanding of the practical applicability of the theories and methods covered.
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:
- Data gathering
- Review of the classical linear regression model
- Univariate time series analysis
- Multivariate time series analysis
- Cointegration: Modeling long-run financial behaviour
- Modelling Volatility: GARCH models
- Information search strategies and source evaluation
Each topic will be accompanied by a hands-on practical application of an empirical finance topic.
During the semester there will be thesis seminars to guide the students towards writing a thesis registration form. This is conducted outside the course.
Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class that is not included on the course homepage/It's learning or text book.
This is a course with continuous assessment (several exam components) and one final exam code. Each exam component is graded by using points on a scale from 0-100. The components will be weighted together according to the information in the course description in order to calculate the final letter grade for the examination code (course). Students who fail to participate in one/some/all exam elements will get a lower grade or may fail the course. You will find detailed information about the point system and the cut off points with reference to the letter grades when the course start.
At resit, all exam components must, as a main rule, be retaken during next scheduled course.
All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.
| Assessments |
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Exam category: Submission Form of assessment: Written submission Weight: 20 Grouping: Group/Individual (1 - 5) Duration: 1 Week(s) Comment: Assignment Exam code: GRA65476 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Exam category: Submission Form of assessment: Written submission Weight: 20 Grouping: Group/Individual (1 - 5) Duration: 1 Week(s) Comment: Assignment Exam code: GRA65476 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Exam category: Submission Form of assessment: Written submission Weight: 10 Grouping: Group/Individual (1 - 3) Duration: 1 Week(s) Comment: Assignment given by the library Exam code: GRA65476 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Exam category: Submission Form of assessment: Written submission Invigilation Weight: 50 Grouping: Individual Support materials:
Duration: 3 Hour(s) Comment: Final written examination with supervision Exam code: GRA65476 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.