## IC205-Introductory Econometrics for Finance

Module Provider: ICMA Centre
Number of credits: 20 [10 ECTS credits]
Level:5
Terms in which taught: Spring term module
Pre-requisites: IC104 Introductory Quantitative Techniques for Business and Finance
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2019/0

Module Convenor: Prof Mike Clements

Type of module:

Summary module description:

This module introduces students to the econometric techniques that are used in the empirical finance literature.

Aims:

Building on Introductory Quantitative Techniques for Finance module, this module aims to give students a solid understanding of the econometric approaches that are commonly employed to test financial theories.

Assessable learning outcomes:

Upon completion of the module, students should be able to:

• Explain the fundamentals of the statistical theory underlying the tools employed to estimate and test econometric models

• Formulate and validate econometric models testing financial theories and hypotheses

• Interpret and analyse the results from an estimated econometric model

• Comprehend and critically evaluate the use of econometrics in the published academic finance literature.

Assessable learning outcomes:

• Explain the fundamentals of the statistical theory underlying the tools employed to estimate and test econometric models?

• Formulate and validate econometric models testing financial theories and hypotheses

• Interpret and analyse the results from an estimated econometric model

The module also aims to encourage the development of IT skills and in particular the manipulation of data using statistical software packages. Students will also improve their ability to translate abstract theoretical concepts into practical solutions to financial problems.

Outline content:

Topic 1 Relationships between variables, regression techniques and simple linear regression: assumptions, estimation (OLS), derivation

Topic 2 The normality assumption

Topic 3 Hypothesis testing for single and multiple hypotheses

Topic 4 Multiple regression : the Classical Linear Regression Model

Topic 5 Goodness of Fit Statistics

Topic 6 Violations of the assumptions: causes, consequences, solutions

Topic 7 Dynamic models

Topic 8 Long run relationships in finance - non-stationarity, testing for unit roots, cointegration, error correction formulations.

Brief description of teaching and learning methods:

The module will be primarily lecture based with directed textbook based supplementary reading. There will be a number of tutorial/seminar sessions – both classroom-based and computer lab-based – to aid students in developing more depth and in understanding the linkage between topics.

Contact hours:
 Autumn Spring Summer Lectures 20 Seminars 8 Practicals classes and workshops 8 Guided independent study: Wider reading (independent) 42 Exam revision/preparation 30 Advance preparation for classes 32 Carry-out research project 20 Reflection 40 Total hours by term 0 200 0 Total hours for module 200

Summative Assessment Methods:
 Method Percentage Written exam 75 Project output other than dissertation 25

Summative assessment- Examinations:

One 2-hour unseen written paper.

Summative assessment- Coursework and in-class tests:

This is a group project. It involves the use of Eviews to undertake some econometric analysis, and interpret the outcomes.

Deadline 2nd week of summer term.

Formative assessment methods:

Class exercises

Penalties for late submission:

Penalties for late submission on this module are in accordance with the University policy.
The following penalties will be applied to coursework which is submitted after the deadline for submission:
• where the piece of work is submitted up to one calendar week after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for the piece of work will be deducted from the mark;
• where the piece of work is submitted more than one calendar week after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:
A minimum mark of 40%.

Reassessment arrangements:

Re-examination for Part 2 modules takes place in August/September of the same year.

Reassessment is by examination only (coursework will not be included in the re-assessment).