F71PT Portfolio Theory

Dr Jing Yao

Course co-ordinator(s): Dr Jing Yao (Edinburgh).


The aim of this course is to provide post graduate students with a broad knowledge of asset pricing and portfolio selection models.

Detailed Information

Course Description: Link to Official Course Descriptor.

Pre-requisites: none.

Location: Edinburgh.

Semester: 2.


• Utility Theory
• Stochastic Dominance
• Measures of Investment Risk
• Mean-Variance Portfolio Theory
• Models of Asset Returns
• Capital Asset Pricing Model
• Efficient Market Hypothesis and Behavioural Finance and Prospect Theory

Learning Outcomes: Subject Mastery

On completion of this module the student should be able to:

  • Derive the properties of a utility function.
  • State the conditions for absolute, first order and second order stochastic dominance.
  • Calculate some important measures of risk: variance, semi-variance, shortfall probability and mean shortfall.
  • Calculate the mean and variance of return on a portfolio of assets.
  • Demonstrate an understanding of methods used to select portfolios of assets, including utility theory, stochastic dominance and mean-variance analysis.
  • Describe the purpose and calculation of the following: opportunity set, efficient frontier, indifference curve, separation theorem.
  • Develop a critical understanding on the theory of mean-variance model and understand its modifications using other risk measures.
  • Describe the properties of single-factor and multi-factor models.
  • Show how to fit a single-factor model to market price data.
    Discuss the assumptions underlying and applications of the Capital Asset Pricing Model.
  • Derive the capital market line and the security market line.
  • Understand the concept of risk premium in Arbitrage Pricing Theory.
  • State the weak, semi-strong and strong forms of the efficient market hypotheses and discuss their economic implications.
  • Discuss the topics in prospect theory: framing, reference points, probability.

Learning Outcomes: Personal Abilities

  • Demonstrate the ability to learn independently
  • Manage time, work to deadlines and prioritise workloads
  • Present results in a way which demonstrates that they have understood the technical and broader issues of asset pricing.
  • Communicate findings effectively in the financial services industry.

Reading list:

  • Joshi & Paterson
    Introduction to Mathematical Portfolio Theory, 1st edition.
    Cambridge University Press.
  • Elton, E., Gruber, M., Brown, S. & Goetzmann, W.
    Modern Portfolio Theory and Investment Analysis, 9th edition.
    Wiley, New Jersey. (older versions are adequate)

Assessment Methods: Due to covid, assessment methods for Academic Year 2021/22 may vary from those noted on the official course descriptor. Please see:
- Maths (F1) Course Weightings 2021/22
- Computer Science (F2) Course Weightings 2021/22
- AMS (F7) Course Weightings 2021/22

SCQF Level: 11.

Credits: 15.

Other Information

Help: If you have any problems or questions regarding the course, you are encouraged to contact the course leader.

Canvas: further information and course materials are available on Canvas