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:


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:2016/7
Module lecturers:
  • Dr Yoske Igarashi - Convenor
Module credit:15
ECTS value:





Cannot be taken with BEA2018 or BEA3018 or BEA3008

Duration of module: Duration (weeks) - term 2:


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 ActivitiesGuided independent studyPlacement / study abroad

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled Learning & Teaching activities22Lectures
Scheduled Learning & Teaching activities5Tutorial (Computer lab practice)
Guided Independent Study123Independent studies (including weekly exercises for Excel/R)

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Weekly exercises on Excel simulation and R programmingn.a.1-10Discussion in class and instructions through emails and office hours

Summative assessment (% of credit)

CourseworkWritten examsPractical exams

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Examination902 hours1-10Exam Grade and Solution Scheme
Computational Assignment 15Submission of one Excel/R file1-10Grade and Office Hours
Computational Assignment 25Submission of one R file1-10Grade and Office Hours

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

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Examination Same as original1-10August Exam Period
Computational Assignment 1Same as original 1-10July/August Reassessment Period
Computational Assignment 2Same as original1-10July/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.



Module has an active ELE page?


Origin date


Last revision date