Introductory description

The main aim of this module is to introduce students to modern theories of Asset Pricing
and Portfolio Theory in both static and dynamic settings. The key is the modelling and
measurement of uncertainty (risk), how investors make decisions in the presence of such
uncertainty, and how such behaviours drive both time series and cross-section of asset
prices and returns in equilibrium.

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.

Financial Markets, Principles of Arbitrage and Valuation

• Modelling financial markets in one period; Trading strategies and arbitrage opportunities; Stochastic discount factor and equivalent martingale measure; The fundamental theorem of asset pricing; Contingent claims, complete and incomplete markets
• Dynamic models in multiple periods; Self-financing strategies; Valuation and hedging in complete markets; Sources of incompleteness, approaches to valuation in incomplete markets
  Modelling and Measuring Risk
• Different types of risk (operational, financial, market, credit, liquidity, …)
• Traditional approach and shortcomings
• Alternative approaches to modelling/measuring risk convex and coherent measures; Value-at-Risk (VaR), expected shortfall; further measures
• Problems with empirical implementation
  Decision-Marking under Uncertainty (Utility Theory)
• Traditional (von Neumann-Morgenstern) theory; Lotteries and preference relations; Utility representation; Risk aversion and risk premium; Representative agents in complete markets
• Shortcomings of traditional theory and Alternatives; Behavioural and cognitive biases; Loss aversion and prospect theory
  Portfolio Allocation and Factor Models
• Single-Factor Models; Mean-variance optimisation without a risk-free asset; Mean-variance optimisation with a risk-free asset;Tangency portfolio and capital markets line; Equilibrium and Capital Asset Pricing Model (CAPM); Tests and critiques of the CAPM
• General (Multi-) Factor Models General framework, factors and risk premia; Specific examples (Fama-French, Carhart, …); Arbitrage-Pricing Theory (APT)

Learning outcomes

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

• Define and explain, intuitively and formally, the fundamental trade-off between risk and return, and how this can be modelled and quantified.
• Understand and explain different models that describe how individuals make decisions in the presence of uncertainty, and how such behaviours affect asset prices and returns in equilibrium.
• Devise and implement empirical methodology to a) estimate the parameters of, and b) assess the validity of, a variety of different asset pricing models.
• Understand and explain how the principle of "absence of arbitrage" is used for valuation and hedging of "contingent claims" in both static and dynamic models

Indicative reading list

Cochrane, J.H. (2001): “Asset Pricing” (2nd “revised” ed.) Princeton University Press
Campbell, J.Y. (2018): “Financial Decisions & Markets: A Course in Asset Pricing” Princeton University Press
Dumas, B. and E. Luciano (2017): “The Economics of Continuous-Time Finance” MIT Press
Föllmer, H. and A. Schied (2016): “Stochastic Finance” (4th ed.) Walter deGruyter, Berlin
McNeil, A., P. Embrechts, and R. Frey (2015): “Quantitative Risk Management” (2nd ed.) Cambridge University Press

Subject specific skills

Design and implement empirical methodology to a) estimate the parameters of, and b) assess the validity of, a variety of asset pricing models.
Design and implement optimal strategies for asset allocation or risk management; devise and apply measures of performance of such strategies.

Transferable skills

Use a variety of quantitative and statistical tools to analyse data and implement/assess quantitative solutions to problems in Asset Pricing.
Demonstrate academic writing skills.
Critically evaluate empirical research.