Timetable information in the Course Catalogue may be subject to change.

University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : Business School : Business Studies

Undergraduate Course: Research Methods in Finance 2 (BUST08050)

Course Outline
SchoolBusiness School CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 8 (Year 2 Undergraduate) AvailabilityNot available to visiting students
SCQF Credits20 ECTS Credits10
SummaryThe course is only open to Year 2 students in the following degree programmes:
MA Accounting and Finance
MA Finance and Business

As a follow-up course of Research Methods in Finance 1, this course aims to help you learn and refine your knowledge of and skills in quantitative methods commonly applied in finance research.
Course description This course aims to help you learn and refine your knowledge of and skills in quantitative research methods that can be applied to your Dissertation research project in the 4th year.

The tentative syllabus includes:
1. Recap of materials taught in Research Methods in Finance 1.
2. Ordinary Least Squares (OLS)
3. Multiple linear regression
4. Violations of OLS assumptions, consequences and correction.
5. Further topics in regression, e.g., non-linear terms, dummy variables and interactions, etc.
6. Time-series analysis.
7. Panel data analysis

You are expected to actively prepare for and engage with the learning materials for the lectures. You will develop practical skills in handling financial data and will learn to perform empirical tests using an econometric software package during the computer lab sessions. You are expected to use the weekly textbook readings independently to support your learning.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Research Methods in Finance 1 (BUST08049)
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2022/23, Not available to visiting students (SS1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 20, Seminar/Tutorial Hours 8, Feedback/Feedforward Hours 4, Formative Assessment Hours 4, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 160 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Individual project (Project Report) 100%:«br /»
1,500-word report (excluding graphs and tables). In the project, you will be asked to address an empirical research question in finance. You will be asked to put together your own data set using databases subscribed by the University, clean/process the data, perform various empirical tests (OLS and panel regressions) on the final sample, and report, discuss and interpret the estimated results (including their statistical and economic significance). You may also be asked to perform further tests (e.g., testing the OLS assumptions, applying non-linear functional terms and dummy variables, etc.) and discuss other empirical issues relating to the estimation.«br /»
Feedback Formative feedback is provided through MCQs during the lectures and discussions and Q&As during the computer lab sessions.
Summative feedback is provided as a written feedback for the individual project.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. You will demonstrate a knowledge and understanding of key econometric techniques for the empirical analysis of economic phenomena, along with application of these techniques in the contexts of finance research.
  2. You will be able to develop practical/technical competencies, including quantitative analysis, interpretation of data and programming of statistical packages, and to demonstrate general IT literacy.
  3. You will be able to present outputs from statistical software in ways that are consistent with the convention in the academic finance literature. You will also be able to communicate in writing the meaning and significance of your statistical findings.
  4. You will demonstrate personal effectiveness through task-management and time-management through the ability to successfully complete an individual empirical research assignment.
Reading List
Core text:
Jeffrey M. Wooldridge. Introductory Econometrics: A Modern Approach, 4e, Cengage Learning, 2009.
Additional Information
Graduate Attributes and Skills Developed and Assessed:
- Appropriate Communication
- Understand and Make Effective Use of Data and Information

An introduction to:
- Personal and Professional Competence
- Academic Excellence
- Intellectual Curiosity
KeywordsNot entered
Course organiserDr Woon Sau Leung
Course secretaryMiss Aoife McDonald
Tel: (0131 6)50 8074
Help & Information
Search DPTs and Courses
Degree Programmes
Browse DPTs
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Important Information