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Unit information: Financial Risk Management in 2021/22

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Financial Risk Management
Unit code MATH30014
Credit points 20
Level of study H/6
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Dr. Skevi Michael
Open unit status Not open
Pre-requisites

MATH10015 Linear Algebra, MATH10011 Analysis ,MATH10013 Probability and Statistics

Co-requisites

None

School/department School of Mathematics
Faculty Faculty of Science

Description including Unit Aims

Unit Aims

To explore the theory and practice of financial risk management in a variety of common settings, including the casino, sports betting, business, and financial markets.

Unit Description

The unit covers the theory of uncertainty assessment, choice under uncertainty, and risk management (see the Learning Objectives below), and illustrates with many practical examples, often involving computing in R. Familiarity with R is not required for the unit, but if you are thinking about a job in finance or data science then you should be aiming to be proficient in R or Python by the time you graduate.

Clarity and effective communication are crucial and you will also need to be comfortable writing descriptive text in well-structured sentences. You will be expected to explore more qualitative aspects of human capacity and desires, as a necessary part of understanding the practice of risk management.

Intended Learning Outcomes

At the end of this unit you should be able to:

  • Use probability theory to structure and quantify uncertainty.
  • Justify the use of expected gain as a method for choosing among small gambles.
  • Evaluate simple gambles, such as those found in casinos.
  • Explain the role of statistical models, and give examples.
  • State, prove, and explain the Von Neumann-Morgenstern theorem for expected utility.
  • Provide simple guidelines for assessing individual utility functions.
  • Use decision trees to evaluate linked decisions, and to value information.
  • State and critique mean-variance portfolio theory.

Teaching Information

The unit will be taught through a combination of

  • synchronous online and, if subsequently possible, face-to-face lectures
  • asynchronous online materials, including narrated presentations and worked examples
  • guided asynchronous independent activities such as problem sheets and/or other exercises
  • synchronous weekly group problem/example classes, workshops and/or tutorials
  • synchronous weekly group tutorials
  • synchronous weekly office hours

Assessment Information

90% Timed, open-book examination 10% Coursework

Raw scores on the examinations will be determined according to the marking scheme written on the examination paper. The marking scheme, indicating the maximum score per question, is a guide to the relative weighting of the questions. Raw scores are moderated as described in the Undergraduate Handbook.

If you fail this unit and are required to resit, reassessment is by a written examination in the August/September Resit and Supplementary exam period.

Resources

If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. MATH30014).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the Faculty workload statement relating to this unit for more information.

Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.

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