Module FINN2031: Financial Econometrics 1

Department: Finance

FINN2031: Financial Econometrics 1

Prerequisites

• None

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• To develop knowledge and understanding of key issues and concepts in Financial Econometrics.
• To equip students with the skills required to appreciate the applied literature in finance, to undertake an applied financial econometrics project and to prepare students for Financial Econometrics at higher levels.
• To offer the opportunity to develop key skills.

Content

• Review of Statistics: random variables, probability distributions and statistical inference.
• Simple linear regression model: OLS, its assumptions and properties (BLUE, GM Theorem, t-test, etc).
• Multiple regression model: assumptions, statistical inference (F-test), goodness of fit).
• A consideration of the breakdown of some of the OLS assumptions: autocorrelation, heteroscedasticity and model mis-specification.
• Simultaneous equation model and endogeneity: causes of endogeneity, 2SLS, IV, and Hausman test).
• Panel data analysis (within and between estimators, fixed effects, diff-in-diff, random effects).

Learning Outcomes

• Have knowledge and understanding of the key theoretical and practical issues in Financial Econometrics.
• Have knowledge of the underpinning mathematical construction of an econometric model.
• Have knowledge of the assumptions and how these assumptions drive the estimation and diagnostic testing of an econometric model.
• Have knowledge of how to obtain and manipulate data in preparation for an econometric analysis.

• Be able to apply econometric methods to the estimation of financial relationships and to interpret the results.
• Be able to undertake an applied financial econometrics projects (estimating relationships using an econometric software package).
• Prepare students for the study of Financial Econometrics at higher levels.
• Critically evaluate contemporary literature that uses econometric techniques either covered in the module or proximate to those covered in the module.
• Evaluate the appropriateness of a particular econometric technique for a specific financial application.

• Written Communication - by completing the summative assignment.
• Planning, Organisation and Time Management.
• Problem Solving and Analysis - by applying the necessary analytical and quantitative skills to identify and empirically test theoretical relationships.
• Initiative - by collecting information for the summative assignment, searching relevant literature and information in preparation for the summative assignment.
• Numeracy - by applying an array of core mathematical-statistical skills;
• Computer Literacy and Information Retrieval - by word-processing the summative assignment and estimating relationships using an econometric software package.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• Lectures provide an introduction to the key theoretical and empirical issues.
• Computer Laboratories introduce students to econometric software used in preparation of the summative assignment.
• Formative assessment is by means of an assignment and a multiple choice test.
• Summative assessment is by means of a written assignment.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

One written assignment of 1500 words and a time constrained multiple-choice question test.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University