2019/20 Undergraduate Module Catalogue

LUBS2225 Credit and Financial Analytics

20 creditsClass Size: 140

Module manager: Fabian Gogolin
Email: F.Gogolin@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2019/20

This module is mutually exclusive with

LUBS2570	Introduction to Econometrics
LUBS2670	Statistics for Business and Economics 2

This module is not approved as a discovery module

Objectives

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.

Learning outcomes
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.

Skills outcomes
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.

Syllabus

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.

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	10	2.00	20.00
Seminar	9	1.00	9.00
Private study hours			171.00
Total Contact hours			29.00
Total hours (100hr per 10 credits)			200.00

Private study

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.

Opportunities for Formative Feedback

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;

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Group Project	Report, 2,000 words	30.00
Total percentage (Assessment Coursework)		30.00

The resit for this module will be 100% by 3 hour examination.

Exams

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

The resit for this module will be 100% by 3 hour examination.

Reading list

The reading list is available from the Library website

Last updated: 12/12/2019

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