| Unit name | Applied Quantitative Research in Accounting and Finance |
|---|---|
| Unit code | EFIMM0120 |
| Credit points | 15 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Dr. Joe Cho |
| Open unit status | Not open |
| Pre-requisites |
None |
| Co-requisites |
None |
| School/department | School of Accounting and Finance - Business School |
| Faculty | Faculty of Social Sciences and Law |
The aim of this unit is to introduce students into statistical analysis of accounting and finance data. The first part of the unit covers principles of conducting applied empirical analysis using a statistical analysis software (STATA). The second part of the unit focuses on practical implementation of selected particular research (statistics and econometric) methodologies. In the unit, students are exposed to various research implications in areas of accounting and finance mainly. They learn how to deal with the quantitative analysis aspect of a research project, with an emphasis on organising data, analysing it with relevant methods and techniques using statistical software and writing up the results in a formal fashion. The unit prepares students to take on an MSc dissertation in an empirical analysis topic. The unit will also provide students with various transferrable skills.
This unit is optional for students on Accounting, Finance & Management. The aim of this unit is to introduce students to quantitative research methods used in accounting and finance research. Students who wish to write a dissertation that is based upon a quantitative approach to analysing data sets collected from databases should take this unit.
On successful completion of the unit students will be able to:
1. Understand the standard principles of interpreting and conducting research in accounting and finance at MSc level
2. Conduct a literature review
3. Work with widely-used accounting and finance databases
4. Familiarize with econometric approaches for panel data and cross-sectional analysis
5. Input data into the appropriate software and shape them accordingly
6. Use appropriate software to analyse data
7. Apply relevant statistical analysis methodologies
8. Interpret the results of their empirical analysis
9. Present and write up the results in a formal fashion
Teaching will be delivered through a combination of synchronous and asynchronous sessions including lectures, tutorials, drop-in sessions, discussion boards and other online learning opportunities
This unit will be assessed by group coursework 50% and individual coursework 50%
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. EFIMM0120).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the Faculty workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an
assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
