Quantitative Methods
| Module title | Quantitative Methods |
|---|---|
| Module code | BEF2015 |
| Academic year | 2025/6 |
| Credits | 30 |
| Module staff | Dr Stanley Gyoshev (Convenor) Dr Wanling Rudkin (Lecturer) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 11 | 11 |
| Number students taking module (anticipated) | 60 |
|---|
Module description
This module provides sound knowledge in the quantitative concepts and applications that are fundamental to financial analysis. It introduces quantitative methods that are used widely in securities and risk analysis and in corporate finance to value capital projects and select investments. This module provides you with a foundation in descriptive statistics which provide the tools to characterise and assess risk and return and other important financial or economic variables. It introduces the fundamental quantitative techniques that are essential for a financial analyst, such as basic statistics, probability theory and regression analysis that support investment and risk decision making in the presence of uncertainty. You will also be introduced to a range of techniques that underlie how financial technology is affecting areas within the investment industry, such as investment analysis, automated advice, and risk management.
This module provides sound knowledge in the quantitative concepts and applications that are fundamental to financial analysis. It introduces quantitative methods that are used widely in securities and financial analysis and in corporate finance to value capital projects and select investments. This module provides you with a foundation in descriptive statistics which provide the tools to characterise and assess risk and return and other important financial or economic variables. It introduces the fundamental quantitative techniques that are essential for financial analysts, such as basic statistics, probability theory and regression analysis that support investment and financing decision making in the presence of uncertainty. The first term approaches these topics mathematically, the second term provides the practical statistical tools for analysis. You will also be introduced to a range of techniques that underlie how financial technology is affecting areas within the investment industry, such as investment analysis, and financial management.
Additional Information:
Internationalisation
The content of this module is relevant across countries as it is based on mathematical and statistical models.
Sustainability
All of the other resources for this module are available on the ELE (Exeter Learning Environment).
Employability
In this module students will learn skills that are transferable and relevant for jobs in investment banks, corporate finance and many other industries. This module also provides a good foundation for students interested in taking CFA level I exam.
Module aims - intentions of the module
This module provides you with a foundation in mathematics and descriptive statistics which provide the tools to characterise and assess risk and return and other important financial or economic variables. The first half of the module provides you with a solid foundation in mathematics for finance and investments. Topics covered include functions and operations, solving simultaneous linear equations, differential calculus and introduction to matrix algebra. The second half of the module introduces the fundamental quantitative techniques that are essential for a financial analyst, such as probability and statistics, hypothesis testing and regression analysis. Elements of portfolio and options mathematics, and techniques of big data will also be examined.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. Apply knowledge and understanding of the key mathematical concepts needed for the quantitative analysis within a finance context
- 2. Apply knowledge and understanding of various statistical methods which are used to investigate financial data
- 3. Apply quantitative techniques within a finance context to solve problems and make decisions
- 4. Interpret financial data and carry out statistical and financial analysis
- 5. Describe aspects of fintech that are relevant for the gathering and analysing of financial data
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 6. Apply quantitative methods used in finance to assess risk and return and other important financial or economic variables
- 7. Application of the quantitative techniques learnt in all areas of your day-to-day activities
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 8. Apply written communication, technical, analytical and problem-solving skills
- 9. Undertake independent study and manage own time
Syllabus plan
-
Semester 1:
- Mathematics
- Functions and operations
- Algebra and solving equations
- Elements of matrix mathematics
- Differential calculus
- Time Value of Money in Finance
- Portfolio mathematics
- Elements of options mathematics
- Introduction to big data techniques
Semester 2: Statistics
- Market returns and descriptive statistics
- Probability concepts fundamentals
- Probability distributions commonly used in finance.
- Hypothesis testing and applications in finance.
- Regression analysis and applications in finance.
- Advanced methods and applications in finance.
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 60 | 240 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled learning and teaching activity | 36 | Lectures |
| Scheduled Learning and Teaching | 4 | Revision |
| Scheduled Learning and Teaching | 20 | Tutorials |
| Guided Independent Study | 240 | Reading, question practice and assessment preparation preparation |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Tutorial questions | In class | 1-9 | In class feedback |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 0 | 100 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Final Exam Maths (term 1 assessment period) | 50 | 2 hours | 1, 3, & 5-9 | Mark awarded and suggested solutions; Students will be offered opportunity to view scripts |
| Final Exam Stats (term 2 assessment period) | 50 | 2 hours | 2-9 | Mark awarded and suggested solutions; Students will be offered opportunity to view scripts |
Details of re-assessment (where required by referral or deferral)
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| Final Exam Maths (term 1) 50% | Final Exam Maths (50%), 2 hours | 1, 3, & 5-9 | Referral/deferral period |
| Final Exam Stats (term 2) 50% | Final exam (50%), 2 hours | 2-9 | Referral/deferral period |
Re-assessment notes
Defer - as first time
Refer - capped at 40%
Indicative learning resources - Basic reading
Basic reading:
- Available on ELE
Other reading (if interested):
- DeFusco, R.A., McLeavey, D.W., Pinto, J.E. Runcle, D.E. and Anson, M.J.P (2016), Quantitative Investment Analysis (3rd ed.). John Wiley & Sons.
- Brooks, C. (2019), Introductory Econometrics for Finance (4th ed.). Cambridge University Press.
- Teall, J. and Hasan I. (2002) Quantitative Methods for Finance and Investments. London: Blackwell Publishing.
- Miller, M. B (2013). Mathematics and Statistics for Financial Risk Management, Wiley Finance.
- Quantitative Methods, CFA® Program Curriculum, CFA Institute.
- “Quantitative Finance: A Simulation-Based Introduction Using Excel” by Matt Davison https://www.routledge.com/Quantitative-Finance-A-Simulation-Based-Introduction-Using-Excel/Davison/p/book/9781439871683
- Teall, J. and Hasan I. (2002) Quantitative Methods for Finance and Investments. London: Blackwell Publishing.
- Miller, M. B (2013). Mathematics and Statistics for Financial Risk Management, Wiley Finance.
- Quantitative Methods, CFA® Program Curriculum Level I Volume I, CFA Institute. (2024)
- Alexander, C (2008) Market Risk Analysis, Quantitative Methods in Finance (The Wiley Finance Series)
- Cox D, and Cox M 2006) The Mathematics of Banking and Finance: 329 (The Wiley Finance Series)
- Swift, L. and Piff, S. (2014) Quantitative Methods for Business, Management & Finance. Basingstoke: Palgrave Macmillan.
- Wisniewski, M (2019). Quantitative Methods for Decision Makers. Harlow: Pearson Education.
Indicative learning resources - Web based and electronic resources
Web-based and electronic resources:
- All lecture and tutorial materials are posted on the intranet.
- ELE
Indicative learning resources - Other resources
Supplementary reading materials are indicated in the references of each lecture.
| Credit value | 30 |
|---|---|
| Module ECTS | 15 |
| Module pre-requisites | BEA1014 |
| Module co-requisites | None |
| NQF level (module) | 5 |
| Available as distance learning? | No |
| Origin date | 25/03/2024 |
| Last revision date | 10/02/2024 |
