Module
Asset Pricing
Module description
Note: cannot be taken with BEA2018 Corporate Finance and BEA3018 Advance Corporate Finance or BEA3008 Finance for Managers
This module has three main aims: (a) to develop in you analytical methods for valuing and managing financial assets; (b) to introduce you to the practical workings of financial markets; (c) to give you a disciplined but practical training in the construction and management of portfolios.
Additional Information:
Employability
The module provides basics for numerical analyses of financial markets in the financial sector.
Research in Teaching
The module introduces students to recent academic studies of financial markets.
Full module specification
| Module title: | Asset Pricing |
|---|---|
| Module code: | BEE3059 |
| Module level: | 3 |
| Academic year: | 2022/3 |
| Module lecturers: |
|
| Module credit: | 15 |
| ECTS value: | 7.5 |
| Pre-requisites: | None |
| Co-requisites: | Cannot be taken with BEA2018 or BEA3018 or BEA3008 |
| Duration of module: |
Duration (weeks) - term 2: 11 |
Module aims
This module has three aims:
1. To provide students with a fundamental knowledge of investment theories and asset pricing theories.
2. To guide students in the practical application of investment analyses.
3. To demonstrate to students the techniques of financial valuation.
ILO: Module-specific skills
- 1. understand fundamental theories in finance such as the Mean-Variance analysis and CAPM
- 2. apply regression methods and statistical tests for empirical CAPM
- 3. apply theories of consumer utility maximisation and general equilibrium to asset pricing
- 4. apply arbitrage arguments to valuation of financial assets
ILO: Discipline-specific skills
- 5. apply mathematical methods of optimisation to portfolio choice problems
- 6. apply statistical estimation and test methods to financial data analyses
- 7. apply economic theories to asset pricing and simulate economic models with computer software
ILO: Personal and key skills
- 8. obtain and process data by using Excel/R
- 9. analyse financial data by using Excel/R
- 10. run simulations with Excel/R
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 27 | 123 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled Learning & Teaching activities | 22 | Lectures |
| Scheduled Learning & Teaching activities | 5 | Tutorial (Computer lab practice) |
| Guided Independent Study | 123 | Independent studies (including weekly exercises for Excel/R) |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Weekly exercises on Excel simulation and R programming | n.a. | 1-10 | Discussion in class and instructions through emails and office hours |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 10 | 90 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Examination | 90 | 2 hours | 1-10 | Exam Grade and Solution Scheme |
| Computational Assignment 1 | 5 | Submission of one Excel/R file | 1-10 | Grade and Office Hours |
| Computational Assignment 2 | 5 | Submission of one R file | 1-10 | Grade and Office Hours |
| 0 | ||||
| 0 | ||||
| 0 |
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 |
|---|---|---|---|
| Examination | Same as original | 1-10 | August Exam Period |
| Computational Assignment 1 | Same as original | 1-10 | July/August Reassessment Period |
| Computational Assignment 2 | Same as original | 1-10 | July/August Reassessment Period |
Syllabus plan
- The mean-variance method of portfolio choice
- The efficient frontier derivation (Lagrangian method)
- Capital Asset Pricing Model (CAPM)
- Measuring the performance of mutual funds (Jensen’s Alpha, Sharpe ratio)
- Market beta
- Empirical CAPM (The Ordinary Least Square method and t-test)
- Dynamic consumption-based models without uncertainty
- Dynamic consumption-based models with uncertainty
- Equity premium puzzle
- Volatility puzzle
Indicative learning resources - Basic reading
- Students are advised to review the materials of economic/statistic modules of their first and second years for basic mathematics (e.g. matrix algebra, Lagrangian method, probability theory, etc.) basic statistics (e.g. variances, covariances, the normal distribution, t distribution, linear regression models, OLS, t-test, F-test, etc.) basic economics (e.g. utility maximisation, expected utility, general equilibrium theory, etc.). Web resources for some of these topics will be posted on ELE.
- R programming
The open-source statistical software R is available for free through the following site. There is also an open-source software for R, named Rstudio. Both R and RStudio are installed in the computer lab in Business School. Instructions and exercises for R programming will be posted on ELE.
R
RStudio
Module has an active ELE page?
Yes
Origin date
16/03/2015
Last revision date
09/10/2017