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MX5013: MATHEMATICS FOR FINANCE (2018-2019)

Last modified: 22 May 2019 17:07


Course Overview

There is an interest in raising the level of understanding of mathematics in the financial sector. This course is a part of the new MSc programme in Financial Mathematics and provides students with the theoretical and practical skills related to discrete time models of financial markets.

Course Details

Study Type Postgraduate Level 5
Session First Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus Old Aberdeen Sustained Study No
Co-ordinators
  • Professor Vassili Gorbunov

What courses & programmes must have been taken before this course?

  • Any Postgraduate Programme (Studied)

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

The course will discuss the basic mathematical concepts necessary for understanding mathematical models of financial markets. The topics will include: discrete probability, measure theory and integration, general probability, differential equations, statistics.

Further Information & Notes

Course Aims
To provide an introduction to “probability theory", namely the mathematical framework used to study events involving infinite uncountable sample spaces, the foundations of statistics, and the theory of ordinary differential equations as mathematical tools for taking advanced courses in financial mathematics.
 
Learning Objectives
Sample spaces and the probability function, $\sigma$ algebra and some measure theory.
 
Application of "conditional probability'' and the partition theorem.
 
Random variables and distribution functions.
 
Expectation and variance.
 
Limit theorems and their application.
 
Stochastic differential equations.
 
The Markov Property.

Degree Programmes for which this Course is Prescribed

  • Master Of Science In Financial Mathematics

Contact Teaching Time

Sorry, we don't have that information available.

Teaching Breakdown

  • 1 Lecture during University weeks 7 - 17
  • 1 Tutorial during University weeks 8 - 17

More Information about Week Numbers


Summative Assessments

One 2h written exam (70%); One individual assignment (30%)

Resit - ‚ÄčOne 2h written exam (100%)

Formative Assessment

There are no assessments for this course.

Feedback

None.

Course Learning Outcomes

None.

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