Quantitative Methods for Finance

Module description

Summary:

The aim of this module is to provide an introduction to econometric techniques that are used in finance. The emphasis is on basic theory and application, the latter being complemented with hands-on exercises using real data. By the end of the module, you will understand and be able to apply basic econometric techniques and issues relating to their application to macroeconomic and financial issues.

Additional Information:

Internationalisation

This is a practical module in quantitative methods where students do a great deal of computing which can be applied internationally.

Employability

This module equips students with skills crucial for employment in the fields of accounting, economics, and finance. These skills include numeracy, computer statistics, interpretation of statistical results, and data analysis.

Sustainability

All the resources for this module are available through the ELE (Exeter Learning Environment).

Full module specification

Module title:Quantitative Methods for Finance
Module code:BEEM104
Module level:M
Academic year:2016/7
Module lecturers:
  • Professor James Davidson - Convenor
Module credit:15
ECTS value:

7.5

Pre-requisites:

None

Co-requisites:

None

Duration of module: Duration (weeks) - term 1:

11

Module aims

The aim of this module is to provide an introduction to econometric techniques that are used in finance. The emphasis is on basic theory and application, the latter being complemented with hands-on exercises using real data. By the end of the module, students should be able to understand and apply basic econometric techniques and issues relating to their application to macroeconomic and financial issues. Emphasis is given not just to understanding the basis of statistical and quantitative techniques but also to their application. This is reflected in the computer-based projects which form an important part of the assessment.

ILO: Module-specific skills

  • 1. Students will have a good understanding of the role of econometric analysis to macroeconomic and finance issues and be able to apply these techniques using real data and to present, interpret and discuss the results that arise from practical case studies.

ILO: Discipline-specific skills

  • 2. Students are expected to demonstrate their ability to understand the basics of econometric analysis; to apply these econometric techniques to macroeconomic and financial data and to appreciate and become competent in the use of econometric packages to economic and finance issues more generally.

ILO: Personal and key skills

  • 3. Students are expected to be able to communicate logical arguments both verbally (through class discussion) and in writing (via module assignments and an exam) that relate to the interpretation and use of quantitative techniques. The computer-bases assignment as well as class exercises will also develop IT skills and the use of computer packages as well as general numeracy skills.

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching ActivitiesGuided independent studyPlacement / study abroad
401100

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Contact hours18Lecture
22Computer laboratory

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Tutorials discussing summative assignments 10 hours 1-3 In-class discussion

Summative assessment (% of credit)

CourseworkWritten examsPractical exams
40600

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
2 assignments, chosen from the total of four computer-based exercises that will be set during the module.401000-1500 words1-3Written Feedback
Examination602 hours1-3Answers on ELE, possibility to discuss with module convenor
0
0
0
0

Details of re-assessment (where required by referral or deferral)

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
2 assignments, chosen from the total of four computer- based exercises that will be set during the module.Assignments1-3 6 weeks after original submission
Examination Examination 1-3 August Examination Period

Syllabus plan

Indicative schedule by week:
1. Statistical fundamentals
2. The two-variable regression model (Example: the capital asset pricing model)
3. Multiple regression
4. Testing hypotheses (Example: modelling consumer demand)
5. Problems with regression, diagnostic tests
6. Univariate time series models
7. Dynamic regression models.
8. Endogenous regressors and instrumental variables
9. Review

Indicative learning resources - Basic reading

Basic reading:

1. Gary Koop, The Analysis of Financial Data, (Wiley 2005) 

2. Robert S. Pindyck and Daniel L. Rubinfeld,  Econometric Models and Economic Forecasts (4th Edition) (Irwin McGraw-Hill, Boston 1997).

3. G. S. Maddala, Introduction to Econometrics (3rd Edition) (Macmillan, New York, 2001).

Module has an active ELE page?

Yes

Origin date

03/09/2007

Last revision date

10/09/2013