Please note this module descriptor is indicative of the structure of this course and may be subject to change.
The aim of this course is to help students develop a working knowledge of statistics and econometrics. There will be an emphasis on application of statistical methods to finance data. The course includes a review of financial mathematics & time value of money applications, matrix algebra, probability theory, theoretical probability distributions and construct econometrics modelling and hypothesis testing
The syllabus for this module includes:
1. Review of Financial mathematics & time value of money applications
2. Statistical Theory: Probability Framework for Statistical Inference; Estimation, Testing Confidence Interval
3. The Classical Linear Regression
4. Multiple regression
5. Time Series Modelling: unit root and co-integration; VAR, GARCH and EGARCH models
6. Pooling Cross-Sections: Simple Panel Data Methods
By the end of this module, students should be able to:
Apply appropriate communication and numerical skills, including the ability to present quantitative and qualitative information, together with analysis, argument and commentary, in a form which will be understood by its intended audience.
A course map contains a list of the individual study units, called modules, that you study to complete your course. Some modules are compulsory, but you can sometimes choose modules outside your core area of study which interest you.
A module is a self-contained, individual unit of study. The module descriptor provides various details about the module including who the module tutor is, what you will be studying, how you will be assessed and what you will have learned once you have completed the module.
Course maps and module descriptors from previous years can be found in the Course Resources Archive.
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