Postgraduate Course: Research Methods in Finance (CMSE11085)
Course Outline
| School | Business School |
College | College of Humanities and Social Science |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 15 |
ECTS Credits | 7.5 |
| Summary | The course builds on the Semester 1 module ¿Statistics for Finance¿ and provides an introduction to some econometric techniques used in empirical research in finance. The first half of the course will be mostly theoretical whereas the second half will be applied. |
| Course description |
At the end of this module you will learn how to apply a number of classical empirical methods in finance by replicating research based on selected published papers. This will provide an introduction to some practical tools of research using real data and to the importance of concise writing and presentation of results using informative graphs and tables. Finally, during this module you will get further training on the econometrics software STATA. These skills will be valuable for writing a good quality postgraduate dissertation and relevant for those wishing to pursue a career in the finance industry.
Syllabus
Theoretical part:
Multiple Regression Analysis with Cross-sectional Data: Estimation and Inference (Review)
Multiple Regression analysis with Qualitative Information: Dummy Variables
Heteroskedasticity
Basic Regression Analysis with Time Series Data
Further Issues in Using OLS with Time Series Data
Autocorrelation
Applied part:
Event studies and market efficiency tests
Ownership, Control and Firm value
Basic empirical asset pricing tests
Combining time-series and cross-sectional data
Panel Data Methods
Student Learning Experience
Weekly 2 hours lectures and weekly 90 minutes tutorials. The tutorials will be a combination of theoretical exercises and STATA based problems. Computer-based tutorials will be held during weeks 1 and 3.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | For Business School PG students only, or by special permission of the School. Please contact the course secretary. |
Course Delivery Information
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| Academic year 2017/18, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
150
(
Lecture Hours 20,
Seminar/Tutorial Hours 20,
Feedback/Feedforward Hours 2,
Formative Assessment Hours 22,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 3,
Directed Learning and Independent Learning Hours
81 )
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| Additional Information (Learning and Teaching) |
Prep Reading: Lectures 30 hrs Tutorials 30 hrs; Project Supervision 2 hrs; Exam Prep 19 hrs
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
50% mid-term class test and 50% individual assignment. |
| Feedback |
All students will be given at least one formative feedback or feedforward event for every course they undertake, provided during the semester in which the course is taken and in time to be useful in the completion of summative work on the course. Such feedback may be at course or programme level, but must include input of relevance to each course in the latter case.
Students will get the answers to the mid-term multiple choice test. Written feedback on the assignment will also be given. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Present and critically interpret the results of statistical and econometric analysis of data.
- Understand and critically discuss of some commonly used research methods and techniques in finance.
- Critically discuss important areas of current empirical research in finance.
- Set up a research question, develop and test hypotheses using real-world data.
- Use evidence to assess the validity of theory and critically evaluate competing theoretical explanations.
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Reading List
Wooldridge, Jeffrey. Introduction to Econometrics. Europe, Middle East and Africa Edition. Cengage Learning.
Additional articles will be listed on Learn as the course progresses. |
Additional Information
| Graduate Attributes and Skills |
Cognitive Skills
After completing this course, students should be able to:
* Read, understand and use journal articles.
* Understand and develop skills to interpret financial data and the ¿stylized facts¿ therein.
* Develop skills for interpreting estimated economic relationships using statistical analysis.¿
* Understand the behaviour of economic and financial variables over time.
* Know how to present and interpret the results of statistical and econometric analysis of data.
* Have an understanding of some commonly used research methods and techniques in finance.
* Get an introduction to important areas and models used in current empirical research in finance.
* Understand how to set up a research question, develop and test hypotheses using real-world data.
* Learn how to present data, perform econometric tests and present these and their economic implications.
Knowledge and Understanding
After completing this course, students should be able to:
* Know how to present and interpret the results of statistical and econometric analysis of data.
* Have an understanding of some commonly used research methods and techniques in finance.
* Get an introduction to important areas of current empirical research in finance.
* Understand how to set up a research question, develop and test hypotheses using real-world data.
* Use evidence to assess the validity of theory.
* Evaluate competing theoretical explanations.
Subject Specific Skills
After completing this course, students should be able to:
* Design and carry out an empirical project based on regression analysis through STATA.
* Execute quantitative finance academic research.
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| Keywords | finResearchMethodsinFinance |
Contacts
| Course organiser | Dr Angelica Gonzalez
Tel: (0131 6)51 3027
Email: |
Course secretary | Miss Rachel Allan
Tel: (0131 6)51 3757
Email: |
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