Introductory description

This module aims to explore and formalize the fundamental relationships between investors’ decision-making in the presence of uncertainty and the cross-sectional and inter-temporal properties of prices and returns of financial assets.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

1. Introduction: Markets, Prices and Returns
2. Preferences and Choice: Time Value
3. Modelling Uncertainty, Measuring Risk
4. Preferences and Choice: Decision-making in the Prescence of Uncertainty
5. Portfolio Theory: Optimal Asset Allocation
6. The Price of Risk: Factor Models
7. Factor Models and Efficiency: Estimation and Testing
8. State Preference Theory: Arbitrage and the Stochastic Discount Factor
9. Application: Contingent Claim Pricing
10. Extensions: Dynamic Models

Learning outcomes

By the end of the module, students should be able to:

• Explain and discuss the paradigm of decision theory in the presence of uncertainty.
• Apply the theory to understand and implement optimal asset allocation, and to explain its implications for the cross-section of asset prices and returns.
• Explain how the theory gives rise to models of “state preference theory”, and to build, analyse, and evaluate such models.
• Explain the general principle of “contingent claim pricing” using the process of “replication”, and to apply this principle to compute the prices of derivative securities.
• Explain how the theory gives rise to the framework of “factor models”, and to build, analyse, and evaluate such models.
• Critically evaluate different theoretical models: understand and be able to explain the assumptions made and intuitively assess their vailidity, understand and be able to explain the implications and discuss their scope and limitations.
• Understand and be able to explain how to develop a framework that would facilitate the empirical verification or rejection of theoretical models.
• Analyse real world events, case studies and/or data, in the context of a given theoretical framework.
• Present the results of such analyses, either in writing or orally, in a concise and structured manner to a non-expert audience

Indicative reading list

Core:
Bodie, Z., A. Kane, and A.J. Marcus: “Investments“; McGraw-Hill. 2014.
Additional:
Back, K.E.: “Asset Pricing and Portfolio Choice Theory”; Oxford University Press. 2010.
Penacchi, G.: “Theory of Asset Pricing”; Prentice Hall. 2007.
Cochrane, J.: “Asset Pricing”; Princeton University Press. 2005.
Copeland, T; Weston, J; Shastri, K.: Financial theory and corporate policy. Pearson. 2014.

Subject specific skills

Build (using spreadsheet or other suitable software) implementations of the models developed in the module to explicitly calculate asset prices or optimal portfolios based on model parameters.
Build (using a spreadsheet or other statistical software) a framework in which it is possible to estimate the parameters of, or empirically assess the validity of such models.
Understand and quantify the risks and other characteristics of a given ("real") market environment and construct optimal investment strategies on the basis of this analysis.
Use a variety of sources to acquire data to investigate a given research hypothesis.
Use spreadsheet or other suitable software to visualise and analyse data.
Use spreadsheet or other suitable software to perform complex calculations.

Transferable skills

Demonstrate problem solving skills.
Demonstrate written and verbal communication skills.