Module manager: Vladimir Pazitka
Email: V.Pazitka@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2024/25
| LUBS2575 | Statistics and Econometrics |
LUBS2224 Credit and Financial Analytics
This module is not approved as a discovery module
This module is intended to equip students with analytical skills and theoretical knowledge necessary to apply econometric techniques to the analysis of financial datasets. Students will get hands on experience working with econometric software, managing and analysing a variety of financial datasets. The skills and knowledge that students will develop can then be applied in other finance modules both in year 2 and final year.
The module aims to provide students with a basic, through to more advanced, level of understanding of econometric techniques as applied in finance. Students will be equipped with the tools required to analyse financial datasets 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 econometric analysis.
On completion of the module students will be able to:
- Demonstrate an advanced level of knowledge of econometric tools employed in finance, incorporating knowledge from the CFA syllabus in quantitative methods;
- Competently use econometric software to conduct empirical investigations and interpret the output;
- Identify and critically evaluate how financial econometrics is used in current applied literature;
- Critically evaluate published empirical papers in finance journals.
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 finance;
- Competently use econometric software to conduct empirical investigations and interpret the output;
- Identify and critically evaluate how financial econometrics is used in current applied literature;
- Critically evaluate published empirical papers in finance journals.
Indicative content:
- Introduction to econometrics and econometric software
- Working with financial data
- Probability distributions and hypotheses testing
- Classical linear regression model
- Multiple linear regression model
- Model validity and diagnostics
- Empirical studies in finance
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Workshop | 9 | 2 | 18 |
| Lecture | 10 | 1 | 10 |
| Independent online learning hours | 20 | ||
| Private study hours | 52 | ||
| Total Contact hours | 28 | ||
| Total hours (100hr per 10 credits) | 100 | ||
This could include a variety of activities, such as reading, watching videos, question practice and exam preparation.
Students will have the opportunity to take a practice exam and will receive a formative feedback on it. Formative feedback will be also provided on exercises covered in workshops and through weekly quizzes.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Report | 1,000 word individual project report | 50 |
| Total percentage (Assessment Coursework) | 50 | |
The resit for this module will be 100% by 2,000 word coursework.
| Exam type | Exam duration | % of formal assessment |
|---|---|---|
| Standard exam (closed essays, MCQs etc) | 1.0 Hrs 0 Mins | 50 |
| Total percentage (Assessment Exams) | 50 | |
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The reading list is available from the Library website
Last updated: 29/04/2024
Errors, omissions, failed links etc should be notified to the Catalogue Team