MN52132: Risk modelling and analysis
[Page last updated: 23 October 2023]
| Academic Year: | 2023/24 |
| Owning Department/School: | School of Management |
| Credits: | 5 [equivalent to 10 CATS credits] |
| Notional Study Hours: | 100 |
| Level: | Masters UG & PG (FHEQ level 7) |
| Period: |
- Semester 2
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| Assessment Summary: | CWRI 100% |
| Assessment Detail: |
- Individual Project (CWRI 100%)
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| Supplementary Assessment: |
- Like-for-like reassessment (where allowed by programme regulations)
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| Requisites: |
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| Learning Outcomes: |
By the end of the unit, you will be able to:
- Develop an understanding of various risk modelling approaches
- Leverage the power of data and evaluate machine learning methods to improve risk management strategies
- Apply traditional and machine learning risk management tools to quantify and analyse financial risks
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| Synopsis: | Develop a broad understanding of various statistical risk modelling techniques and how to use them in risk analysis and management
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| Content: | Key elements to be included:
- Quantifying risk
- Traditional risk management models
- Advanced risk management models
- Forecasting models
- Machine learning models
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| Course availability: |
MN52132 is Compulsory on the following courses:
School of Management
MN52132 is Optional on the following courses:
School of Management
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Notes: - This unit catalogue is applicable for the 2023/24 academic year only. Students continuing their studies into 2024/25 and beyond should not assume that this unit will be available in future years in the format displayed here for 2023/24.
- Courses and units are subject to change in accordance with normal University procedures.
- Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.
- Find out more about these and other important University terms and conditions here.
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