This page is for the academic year 2021-22. The current handbook year is 2022-23No such Code for pgprog: N3KA09
Department: Economics and Finance
FINANCIAL MODELLING AND BUSINESS FORECASTING (ONLINE)
||Not available in 2021/22
Excluded Combination of Modules
- Financial Modelling and Business Forecasting (Taught) - ECON45615
- 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; ï‚§
- to provide students with the most recent tools required to analyse and predict financial markets.
- The statistical properties of univariate time series models and their application in Finance; ï‚§
- Models of nonstationary time series; ï‚§
- Cointegration and error-correction model ï‚§
- Cointegration in multivariate systems; ï‚§
- Modelling volatility; ï‚§
- Future topics on ARCH; ï‚§
- Forecasting in financial econometrics.
- On completion of the module students should: ï‚§
- have an advanced knowledge of the principles and methods of modern financial econometrics; ï‚§
- 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; ï‚§
- have extended their understanding of the application of econometric methods and interpretation of the results at an advanced level; ï‚§
- 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: ï‚§
- 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
- The module is delivered via online learning, divided up into study weeks with specially produced resources within each week. Resources vary according to the learning outcomes but normally include: video content, directed reading, reflection through activities, opportunities for self-assessment and peer-to-peer learning within a tutor-facilitated discussion board. Tutors provide feedback on formative work and facilitate discussion board communication as well as being available for individual consultation as necessary (usually by email and Skype).
- 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
|Video content, directed reading, self-assessed assignments and guidance for further reading
||Component Weighting: 100%
||Length / duration
|Written assignment requiring application of advanced econometric methods
Short-answer questions and case study exercises.
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University