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2007/08 Taught Postgraduate Module Catalogue

LUBS5042M Financial Econometrics

15 creditsClass Size: 100

Module manager: Prof. Yongcheol Shin
Email: ys@lubs.leeds.ac.uk

Taught: Semester 1 View Timetable

Year running 2007/08

Pre-requisite qualifications

The qualifications to gain entrance to the MSc in Financial Mathematics are sufficient.

This module is not approved as an Elective

Objectives

The module overviews and develops the essential econometric techniques used in applied financial analysis. The module aims to deliver central problems in contemporary empirical analysis of financial markets. These problems are identified as the existence of speculation and its distortion of efficient markets, other forms of market inefficiency and modelling of time-varying risk. The module will also put special emphasis on modern analytical techniques.

The learning outcomes are knowledge and understanding of the concepts and techniques listed below and the application of these concepts and techniques to the modelling of stock prices, exchange rates and other related financial time series. The module also aims to develop an essential skill to make presentations and critically evaluate leading research papers in the field, in a seminar context.

At the end of the module, a typical student will be able to

- evaluate basic models and principles in the analysis of the financial time series;
- interpret the existing empirical literature and execute new empirical studies in the areas of asset pricing, market microstructure and the general modelling of financial time series;
- in particular, conduct an independent empirical analysis from collecting the data, estimating econometric specifications to writing a self-fulfilling report.

Syllabus

An overview of basic techniques
- Autocovariance, autocorrelation and partial autocorrelation.
- Brief review of OLS, Maximum Likelihood and GMM estimation
- Hypothesis testing.
- Application to stock returns.

Unit roots, Cointegration and VAR
- Difference stationary and trend stationary processes.
- Testing for unit roots: the DF and KPSS test statistics.
- VAR model, Granger causality, and impulse response analysis.
- Cointegrating VAR model.
- Applications to the purchasing power parity and to the net present value model of stock prices, market microstructure and the efficient markets hypothesis.

Stochastic volatility
- ARCH, GARCH models.
- Applications to financial market volatility and time dependent risk premiums.

Advanced Modelling Issues
- Nonlinear Asymmetric Regime-Switching Models
- Asymmetric Cointegration and Error Correction Models
- Panel Data Approach to Factor Pricing Models and Time-varying Risk Premia

Teaching methods

Delivery typeNumberLength hoursStudent hours
Lecture102.0020.00
Tutorial101.0010.00
Private study hours120.00
Total Contact hours30.00
Total hours (100hr per 10 credits)150.00

Private study

8 hours per lecture: 80 hours;
4 hours per practical class: 40 hours.

Opportunities for Formative Feedback

Exercises will be handed in for assessment on a bi-weekly basis.

Methods of assessment


Coursework
Assessment typeNotes% of formal assessment
ReportEmprical Project10.00
EssayIn course exercises20.00
Total percentage (Assessment Coursework)30.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated


Exams
Exam typeExam duration% of formal assessment
Standard exam (closed essays, MCQs etc)2 hr 70.00
Total percentage (Assessment Exams)70.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

The reading list is available from the Library website

Last updated: 29/01/2007

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