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2020/21 Undergraduate Module Catalogue

LUBS2224 Credit and Financial Analytics

10 creditsClass Size: 195

Module manager: Pia Helbing
Email: P.Helbing@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2020/21

Co-requisites

LUBS2226Applied Credit Analytics

This module is mutually exclusive with

LUBS2575Statistics and Econometrics

Module replaces

LUBS2225 Credit and Financial Analytics

This module is not approved as a discovery module

Module summary

This module is intended 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. It provides skills and knowledge that are applied in other finance modules both in Year 2 and final year.

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 knowledge 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
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 heteroscedasticity. 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

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information

Delivery typeNumberLength hoursStudent hours
Workshop51.005.00
Lecture102.0020.00
Private study hours75.00
Total Contact hours25.00
Total hours (100hr per 10 credits)100.00

Private study

This could include a variety of activities, such as reading, watching videos, question practice and exam preparation.

Opportunities for Formative Feedback

Your teaching methods could include a variety of delivery models, such as face-to-face teaching, live webinars, discussion boards and other interactive activities. There will be opportunities for formative feedback throughout the module.

Methods of assessment

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information


Exams
Exam typeExam duration% of formal assessment
Standard exam (closed essays, MCQs etc) (S1)2 hr 00 mins100.00
Total percentage (Assessment Exams)100.00

The resit for this module will be 100% by 2 hour examination.

Reading list

The reading list is available from the Library website

Last updated: 15/09/2020

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