Module ECON45615: FINANCIAL MODELLING AND BUSINESS FORECASTING (TAUGHT)

Department: Economics

ECON45615: FINANCIAL MODELLING AND BUSINESS FORECASTING (TAUGHT)

Tied To

• N3KA09: Finance (Global) (see Postgraduate Handbook 2016-2017 for details)

Pre-requisites

Corequisites

Excluded Combinations

Aims

• to build upon the knowledge gained in Econometrics I and provide students with the specific advanced technical skills necessary to understand the latest techniques employed by financial econometricians; 
• to provide students with the most recent tools required to analyse and predict financial markets.

Content

• The statistical properties of univariate time series models and their application in Finance; 
• Models of nonstationary time series; 
• Cointegration and error-correction model 
• Cointegration in multivariate systems; 
• Modelling volatility; 
• Future topics on ARCH; 
• Forecasting in financial econometrics.

Learning Outcomes

• On completion of the module students should: 
• have an advanced knowledge of the principles and methods of modern financial econometrics; 
• have extended and deepened their understanding of Econometrics gained in Econometrics I, and improved their critical judgement and discrimination in the choice of techniques applicable to complex situations; 
• have extended their understanding of the application of econometric methods and interpretation of the results at an advanced level; 
• have extended their understanding of the use of econometric tools to conduct advanced empirical investigations into complex specialised issues.

• By the end of the module, students should: 
• have further practised problem solving skills at an advanced level and the use of econometric software.

• In addition, students will have had the opportunity to further develop the following key skills:
• effective written communication skills
• planning, organising and time management skills
• problem solving and analytical skills
• the ability to use initiative
• advanced skills in the interpretation of data
• advanced computer literacy skills

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• Learning outcomes will be met through a combination of taught input, groupwork, case studies and discussion, supported by guided reading and specially-written self-study material.
• The summative assignment will test students' ability to apply advanced econometric methods and tools in order to conduct their own empirical investigation.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment

Short-answer questions and case study exercises.