Module Database Search
| MODULE DESCRIPTOR | |||
|---|---|---|---|
| Module Title | |||
| Quantitative Methods For Finance | |||
| Reference | BSM004 | Version | 10 |
| Created | December 2023 | SCQF Level | SCQF 11 |
| Approved | July 2019 | SCQF Points | 15 |
| Amended | March 2024 | ECTS Points | 7.5 |
| Aims of Module | |||
|---|---|---|---|
| To enable students to develop the quantitative skills required to effectively analyse financial problems. | |||
| Learning Outcomes for Module | |
|---|---|
| On completion of this module, students are expected to be able to: | |
| 1 | Evaluate key descriptive statistics within the context of finance. |
| 2 | Solve specific financial problems with statistical inference and hypothesis testing techniques. |
| 3 | Construct econometrics models in Excel and specialized statistical computer software SPSS to solve financial problems. |
| 4 | Criticise regression results generated from Excel and SPSS. |
| Indicative Module Content |
|---|
| Basic financial mathematics; data presentation and descriptive statistics; probability distributions and asset returns; statistical inference techniques; principal components and factor analysis; Environment, social and corporate governance (ESG) rating methodologies, basic time series analysis; high low method; regression analysis; model transformation; use of SPSS and Excel software. |
| Module Delivery |
|---|
| Topics are introduced in lectures and developed in computer laboratories and in tutorials for which students are expected to undertake directed independent learning. |
| Indicative Student Workload | Full Time | Part Time |
|---|---|---|
| Contact Hours | 36 | N/A |
| Non-Contact Hours | 114 | N/A |
| Placement/Work-Based Learning Experience [Notional] Hours | N/A | N/A |
| TOTAL | 150 | N/A |
| Actual Placement hours for professional, statutory or regulatory body |
| ASSESSMENT PLAN | |||||
|---|---|---|---|---|---|
| If a major/minor model is used and box is ticked, % weightings below are indicative only. | |||||
| Component 1 | |||||
| Type: | Examination | Weighting: | 100% | Outcomes Assessed: | 1, 2, 3, 4 |
| Description: | Closed book examination. | ||||
| MODULE PERFORMANCE DESCRIPTOR | |
|---|---|
| Explanatory Text | |
| Component 1 comprises 100% of the module grade. To pass the module, a D grade is required. | |
| Module Grade | Minimum Requirements to achieve Module Grade: |
| A | A |
| B | B |
| C | C |
| D | D |
| E | E |
| F | F |
| NS | Non-submission of work by published deadline or non-attendance for examination |
| Module Requirements | |
|---|---|
| Prerequisites for Module | None. |
| Corequisites for module | None. |
| Precluded Modules | None. |
| INDICATIVE BIBLIOGRAPHY | |
|---|---|
| 1 | BROOKS, C., 2019. Introductory Econometrics For Finance. 4th ed. Cambridge University Press. |
| 2 | OAKSHOTT, L., 2020. Essential quantitative methods for business management and finance. 7th ed. Basingstoke: Palgrave Macmillan. |
| 3 | BOWERMAN, B., DROUGAS, A, M., DUCKWORTH, W, M., et al., 2019. Business Statistics and Analytics in Practice. 9th ed. McGraw Hill. |
| 4 | PALLANT, J., 2020. SPSS survival manual : a step by step guide to data analysis using IBM SPSS. 7th ed. Routledge. |