Module manager: Fabian Gogolin
Email: F.Gogolin@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2019/20
| LUBS2570 | Introduction to Econometrics |
| LUBS2670 | Statistics for Business and Economics 2 |
This module is not approved as a discovery module
The aim of this module is to give students a knowledge of research methods and statistical financial analytical techniques and how they can be used to analyse business related, financial and economic data sets. Further, the module aims to provide students with a basic, through to more advanced, level of understanding of the techniques of modern econometric practices as applied in finance and credit decision-making and risk management. Students will be equipped with the tools (statistical and econometric methods and the use of appropriate econometric software) required to model, analyse and predict financial market and corporate behaviour and to test theories and hypotheses in this field. Students will be given computer-based tasks in addition to class tasks and are expected to develop competence in the use of statistical and econometric software for data management and processing, time series and multiple regression analysis. The content provides skills and knowledge that are applied in other finance modules both in Year 2 and final year.
On completion of the module students will be able to:
- Demonstrate an advanced level of knowledhe of econometric tools employed in finance and credit management, incorporating knowledge from the CFA syllabus in quantitative methods;
- Competently use econometric tools (software packages SPSS or STATA) to conduct empirical investigations and interpret the output;
- Identify and critically evaluate how financial econometrics is used in current applied literature on financial modelling and forecasting;
- Critically evaluate published empirical papers in the finance journals and regulations governing risk management and financial conduct in the banking, credit and financial services sectors.
Transferable skills:
- Written communication skills
- Critical thinking skills
- Advanced numeracy skills
- Team working skills
Subject specific skills:
On completion of this module students will be able to:
- Demonstrate advanced problem solving, analytical and quantitative skills by applying current theory and appropriate analytical tools to complex problems in credit risk management.
Indicative content:
- Introduction to Econometrics and Applications in Finance
- Statistical Foundations, Descriptive Statistics, Distributions and Hypotheses Tests Data Types and Issues, Topics and Concepts in Finance.
- Correlation and Simple Regression. Least Squares Methods and Diagnostics. Testing. Hypothesis Testing. Issues Relating to Autocorrelation.
- Multiple Regression. Specification and Testing of Regression Models. Functional Forms and Transformations. Dummy Variables. Issues Relating to Multi-collinearity, autocorrelation and heterscedasticity. Applications and Examples.
- Analysis of Limited Dependent Variables. Probability. Linear probability and Logistic Regression. Models, Tests and Interpretation. Applications in Finance: Credit Risk and Probability of Default. Other Limited Dependent Variables.
- Elementary time series estimation.
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Lecture | 10 | 2 | 20 |
| Seminar | 9 | 1 | 9 |
| Private study hours | 171 | ||
| Total Contact hours | 29 | ||
| Total hours (100hr per 10 credits) | 200 | ||
Students are required to undertake specified pre-reading and question preparation in advance of the classes based on the material introduced in the lectures. This includes some online pre-reading and formative questions.
Students will be able to monitor their progress through fortnightly seminars. Model answers and answers and marking schemes for workshop papers against which students can assess their own performance;
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Group Project | Report, 2,000 words | 30 |
| Total percentage (Assessment Coursework) | 30 | |
The resit for this module will be 100% by 3 hour examination.
| Exam type | Exam duration | % of formal assessment |
|---|---|---|
| Standard exam (closed essays, MCQs etc) | 2.0 Hrs Mins | 70 |
| Total percentage (Assessment Exams) | 70 | |
The resit for this module will be 100% by 3 hour examination.
The reading list is available from the Library website
Last updated: 12/12/2019
Errors, omissions, failed links etc should be notified to the Catalogue Team