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Unit information: Applied Quantitative Research in Accounting and Finance in 2020/21

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

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. Dimos Andronoudis
Open unit status Not open




School/department School of Accounting and Finance
Faculty Faculty of Social Sciences and Law

Description including Unit Aims

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 the Accounting, Finance & Management. Students who take that unit and wish to write a dissertation on a quantitative project in Accounting and Finance should also take that unit.

Intended Learning Outcomes

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 Information

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

Assessment Information

This unit will be assessed by group coursework 50% and individual coursework 50%

Reading and References

There is no specific textbook for the unit. Instead, the reading combines detailed study of specific academic research papers used to illustrate each of the topics with selected parts of background references, such as:

  • Zacks, Leonard (2011), The handbook of equity market anomalies: Translating market inefficiencies into effective investment strategies, John Wiley & Sons, Hoboken, NJ.
  • Saunders, Mark and Lewis, Philip and Thornhill, Adrian (2015). Research methods for business students, seventh edn., Pearson, Essex.
  • Dougherty, Christopher (2016), Introduction to econometrics, fifth edn. Oxford University Press, Oxford.
  • Baum, Christopher M. (2006), Introduction to modern econometrics using Stata, third edn., Stata Press.