Course co-ordinator(s): Prof Andrew Cairns (Edinburgh), Peter Ridges (Edinburgh).
Aims:
The aim of this course is to provide post graduate student with a broad knowledge of asset pricing and portfolio selection models.
Detailed Information
Pre-requisites: none.
Location: Edinburgh.
Semester: 2.
Syllabus:
• 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 estimates
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 the Computer Science Course Weightings and the Maths Course Weightings for 2020-21 Semester 1 assessment methods.
SCQF Level: 11.
Credits: 15.
Other Information
Help: If you have any problems or questions regarding the course, you are encouraged to contact the lecturer
Canvas: further information and course materials are available on Canvas