Introductory description

The purpose of this module is to provide a general introduction to econometric techniques used for modeling and understanding financial markets. Upon finishing the module, students should have a solid grasp of several important models in financial econometrics.

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.

Part 1: GMM for Financial Time Series (weeks 1-3)

• Conditional Moment Restrictions and Optimal Instruments
• Application to GARCH-type Models
• Application to Stochastic Discount Factor Models
• Inference in Misspecified Models

Part 2: Non-Linear State Space Models (weeks 4-6)

• Stochastic Volatility
• Filtering
• Indirect Inference

Part 3: Continuous Time Models (weeks 7-10)

• High-Frequency Asymptotics
• Maximum Likelihood
• Option Price Data

Learning outcomes

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

• Demonstrate understanding of the properties of time-series modelling; their advantages and disadvantages, and implement the associated estimation procedures
• Demonstrate understanding of and apply linear and non-linear estimation and filtering methods
• Demonstrate understanding of the main approaches in estimation of continuous time models and being able to estime them using high-frequency data
• Think quantitatively and critically

Indicative reading list

John Y. Campbell: Financial Decisions and Markets, Princeton University Press.
John Y. Campbell, Andrew W. Lo and A. Craig MacKinlay: The Econometrics of Financial Markets, Princeton University Press.
John H. Cochrane: Asset Pricing, Princeton University Press.
Christian Gourieroux and Joann Jasiak: Financial Econometrics, Princeton University Press.
James D. Hamilton: Time Series Analysis, Princeton University Press.
Alexander J. McNeil, Rudiger Frey and Paul Embrechts: Quantitative Risk Management, Princeton University Press.
Stephen J. Taylor: Asset Price Dynamics, Volatility and Prediction, Princeton University Press

Interdisciplinary

Contents from several disciplines, such as economics, finance, and statistics, are included in the module.

Subject specific skills

estimate quantitative models and conduct statisitcal inference

select an appropriate estimation method and inference framework from the set of exiting models and frameworks

Transferable skills

Problem solving