Introductory description

The aim is to introduce the main tools and approaches to estimation and inference of financial and economic models.

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:

• Understand the properties of time-series modelling; their advantages and disadvantages.
• Implement the associated estimation procedures.
• Understand and apply linear and non-linear estimation and filtering methods .
• Understand main approaches in estimation of continuous time models and being able to estimate them using high frequency data.
• Be able to read and Critically assess literature, being able to select an appropriate estimation method and inference framework from the set of exiting models and frameworks.

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

Subject specific skills

Use relevant software packages to estimate and make statistical inference .

Transferable skills

Understanding of commonly used empirical techniques in Finance.
Ability to analyse data using these techniques in practice.