FIN-40055 - Module Specification
Keele Business School
Faculty of Humanities and Social Sciences

Programme/Approved Electives for 2024/25

Available as a Free Standing Elective

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2024/25

This module provides students with a solid background in modern econometrics. Students will cover both regression analysis and time series in depth. The main focus will be on application and interpretation of econometric models rather than the theoretical derivation of such models. Students will make continuous use of the Bloomberg Trading machines and will carry out their analysis using statistical package and occasionally using Excel spreadsheets. This module will prepare students to complete their dissertation/project to a high standard.

Intended Learning Outcomes

identify and justify the basic components of research frameworks, relevant to the tackled research problem and develop a credible research proposal: 1
demonstrate and apply knowledge of modern probability theory, probability distributions and their application to modern business: 1
visualise and interpret data, demonstrating comprehensive understanding of key statistical concepts, sampling, estimation and hypothesis testing: 1
demonstrate a critical appreciation of the strengths and weaknesses of single and multiple regression models to solve business problems: 1
undertake modern time series modelling, estimation of complex time series models and appreciate their wider application in portfolio management and risk modelling: 1
apply advanced econometric methods such as panel data, machine learning and big data: 1

Study hours

2 hour lectures per week for 12 weeks.
126 hours independent study

School Rules

None

Description of Module Assessment