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Mathematics of Risk (MAST90051)
Graduate courseworkPoints: 12.5Dual-Delivery (Parkville)
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About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 2
Konstantin Borovkov
Email: borovkov@unimelb.edu.au
Overview
Availability | Semester 2 - Dual-Delivery |
---|---|
Fees | Look up fees |
Mathematical modelling of various types of risk has become an important component of the modern financial industry. The subject discusses the key aspects of the mathematics of market risk. Main concepts include loss distributions, risk and dependence measures, copulas, risk aggregation and allocation principles, elements of extreme value theory. The main theme is the need to satisfactorily address extreme outcomes and the dependence of key risk drivers.
Intended learning outcomes
After completing this subject students will:
- understand the basic mathematical concepts used in the financial market risk analysis;
- know how these concepts can be applied in situations requiring quantitative risk management;
- gain the ability to pursue further studies in this and related areas.
Generic skills
In addition to learning specific skills that will assist students in their future careers in science, they will have the opportunity to develop generic skills that will assist them in any future career path. These include:
- problem-solving skills: the ability to engage with unfamiliar problems and identify relevant solution strategies;
- analytical skills: the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of analysis;
- collaborative skills: the ability to work in a team;
- time-management skills: the ability to meet regular deadlines while balancing competing commitments.
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST30020 | Probability for Inference | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
AND
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST20026 | Real Analysis |
Semester 2 (Dual-Delivery - Parkville)
Semester 1 (Dual-Delivery - Parkville)
|
12.5 |
MAST20033 | Real Analysis: Advanced | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 31 January 2024
Assessment
Description | Timing | Percentage |
---|---|---|
Up to 30 pages of written assignments (two assignments worth 10% each, due mid and late in semester)
| Second half of the teaching period | 20% |
A written examination
| During the examination period | 70% |
10 weekly online quizzes, starting from week 2
| From Week 2 to Week 11 | 10% |
Additional details
This Dual-Delivery subject has On Campus assessment components.
Last updated: 31 January 2024
Dates & times
- Semester 2
Coordinator Konstantin Borovkov Mode of delivery Dual-Delivery (Parkville) Contact hours 36 hours: One 2-hour lecture per week and one 1-hour practical class per week. Total time commitment 170 hours Teaching period 25 July 2022 to 23 October 2022 Last self-enrol date 5 August 2022 Census date 31 August 2022 Last date to withdraw without fail 23 September 2022 Assessment period ends 18 November 2022 Semester 2 contact information
Konstantin Borovkov
Email: borovkov@unimelb.edu.au
Time commitment details
170 hours
Additional delivery details
This Dual-Delivery subject has On Campus assessment components.
Last updated: 31 January 2024
Further information
- Texts
Prescribed texts
Recommended texts and other resources
Alexander J McNeil, Rüdiger Frey, Paul Embrechts. Quantitative Risk Management: concepts, techniques and tools, Princeton Univ. Press (2005)
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Data Science Course Ph.D.- Engineering Course Master of Science (Mathematics and Statistics) Course Doctor of Philosophy - Engineering Course Master of Commerce (Finance) Course Master of Philosophy - Engineering Informal specialisation Mathematics and Statistics - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 31 January 2024