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Module Title
LM Financial Modelling Techniques
School
Birmingham Business School
Department
Finance
Module Code
07 36332
Module Lead
Professor Jane Binner
Level
Masters Level
Credits
20
Semester
Semester 1
Pre-requisites
Co-requisites
Restrictions
None
Contact Hours
Lecture-20 hours
Practical Classes and workshops-10 hours
Supervised time in studio/workshop-10 hours
Guided independent study-160 hours Total: 200 hours
Exclusions
Description
This module teaches students a wide range of techniques for summarising data, analysing data, estimating models and testing hypotheses. The module has three sections. In the first section, students will learn the techniques for calculating measures of central tendency and dispersion of a dataset, such as mode, median, mean, range, standard deviation, skewness and kurtosis. Statistical inference from the classical linear regression model will cover concepts of hypothesis testing and construction of confidence intervals for regression coefficients.
In Section two, further developments of the classical linear regression model will include the breakdown of the classical regression model’s assumptions, e.g. multicollinearity, heteroscedasticity and autocorrelation and remedies for these problems.
In the final section, students will learn parametric techniques for analysing data, constructing financial models and testing the goodness of fit of models. Topics that will be covered will include multiple regression analysis, moving average processes, autoregressive processes, ARCH and GARCH processes and an introduction to forecasting. Consideration of other topics, such as quantitative research methods, including panel data estimation technique, logit and probit models, simultaneous equations models, as well as the strengths and limitations of each technique, will conclude the module.
Learning Outcomes
By the end of the module students should be able to:
determine the appropriate approach(s) to summarise a set of data and apply the statistical method(s)
Select the appropriate probability model(s) to use to estimate the likelihood of occurrence of some events that a finance manager is interested in and apply the model(s)
Identify the appropriate parametric and non-parametric technique(s) to use to test a hypothesis, construct suitable financial models, apply the technique(s) and interpret results obtained correctly
demonstrate critical awareness of the strengths and limitations of any technique that they use.
Interpret correctly the results obtained using the selected techniques.
Assessment
36332-01 : Continuous Assessment : Class Test (20%)
36332-02 : Group Assignment : Group Assessment - Coursework (30%)
36332-03 : Exam : Exam (Centrally Timetabled) - Written Unseen (50%)
Assessment Methods & Exceptions
Assessment: 1,500 words individual coursework (50%) 1.5 hour written examination (50%)
Reassessment: Students who fail the module will resit the failed component(s) only.
