Quantitative Risk - MATHRH3564
This Stream is no longer accepting new enrolments
Stream Summary
Faculty: SCI - Faculty of Science
School: School of Mathematics and Statistics
Contact: http://www.maths.unsw.edu.au/
Program: 3564 - Economics/Advanced Maths(Hons)
Award(s):
Bachelor of Science (Advanced Mathematics) (Honours)
View stream information for previous years
Stream Outline
The School of Mathematics and Statistics (MathsStats) offers a number of Honours streams including in Quantitative Risk (QR). The Honours year introduces students to the investigative and research aspects of knowledge and consists of advanced lecture courses, an Honours thesis and seminar participation. We offer expert supervision across a wide range of areas in modern mathematics and statistics. Our Honours students are supervised in their Honours project by some of Australia's finest mathematicians.
Students who enrol in the Quantitative Risk Honours Stream are expected to have completed a mathematics or statistics major with a focus on financial and risk applications in an advanced undergraduate science or other mathematically focused program. Students who have completed other cognate disciplines and who are completing a project within the usual concerns of this discipline may also apply for entry to this stream.
Honours in Quantitative Risk is restricted to the advanced mathematics degree, or dual degrees with advanced mathematics, and can be completed full-time or part-time. Most students commence their enrolment in semester 1 (S1) but mid-year entry is available subject to resources. Students should check the MathStats Honours webpages for application procedures and enrolment deadlines.
Entry Requirements
So that students have sufficient background to attempt the courses in the honours year, students must discuss their selection of Level III courses with the School of Mathematics Honours Coordinator or another academic adviser.
To enter honours in QR, students must have completed Stage 3 of the quantitative risk plan in the Advanced Mathematics degree.
In addition, students will normally be required to have:
Students who enrol in the Quantitative Risk Honours Stream are expected to have completed a mathematics or statistics major with a focus on financial and risk applications in an advanced undergraduate science or other mathematically focused program. Students who have completed other cognate disciplines and who are completing a project within the usual concerns of this discipline may also apply for entry to this stream.
Honours in Quantitative Risk is restricted to the advanced mathematics degree, or dual degrees with advanced mathematics, and can be completed full-time or part-time. Most students commence their enrolment in semester 1 (S1) but mid-year entry is available subject to resources. Students should check the MathStats Honours webpages for application procedures and enrolment deadlines.
Entry Requirements
So that students have sufficient background to attempt the courses in the honours year, students must discuss their selection of Level III courses with the School of Mathematics Honours Coordinator or another academic adviser.
To enter honours in QR, students must have completed Stage 3 of the quantitative risk plan in the Advanced Mathematics degree.
In addition, students will normally be required to have:
- An average above 70 in the level III mathematics courses and
- An average above 70 in the compulsory level III courses taken as part of their QR major.
The compulsory level III courses in the QR major includes MATH3901.
With the permission of the Head of School (or nominee), a student may be allowed into Quantitative Risk Honours without having satisfied the specific requirements, and instead have shown some evidence of the ability to undertake independent study.
With the permission of the Head of School (or nominee), a student may be allowed into Quantitative Risk Honours without having satisfied the specific requirements, and instead have shown some evidence of the ability to undertake independent study.
Stream Structure
The thesis component of Quantitative Risk Honours requires a student to undertake these two courses:
- MATH4001 MathsStats Hons Thesis A (6 UOC)
- MATH4002 MathsStats Hons Thesis B (12 UOC)
These courses form two parts of the same thesis/project. Students (full or part-time) must complete the honours thesis in any two consecutive semesters of their honours enrolment, preferably by enrolling in MATH4001 before MATH4002 but there may be special cases where the School of MathsStats will allow the order to be reversed.
Students will also be required to participate in the weekly honours seminar, which will be timetabled as a joint class in the thesis courses. This seminar is intended to allow students to practise their final honours seminar presentation, listen to presentations of other honours students and engage in other honours training activities. Students should also attend any appropriate seminars in their thesis area.
The thesis will be assessed by at least two academic staff. The supervisor or supervisors of the thesis is expected to submit a report, but will not be a marker for the thesis. Students are required to give a short seminar on their thesis and this will account for 10% of the final mark for the thesis, the remaining 90% coming from the written thesis report.
The 30uoc coursework component of Quantitative Risk Honours will consist of five 6uoc lecture courses selected from the list below, or others, with the approval by the Head of School or nominee and taken with the advice of the honours thesis supervisor.
Approved Courses
Students will also be required to participate in the weekly honours seminar, which will be timetabled as a joint class in the thesis courses. This seminar is intended to allow students to practise their final honours seminar presentation, listen to presentations of other honours students and engage in other honours training activities. Students should also attend any appropriate seminars in their thesis area.
The thesis will be assessed by at least two academic staff. The supervisor or supervisors of the thesis is expected to submit a report, but will not be a marker for the thesis. Students are required to give a short seminar on their thesis and this will account for 10% of the final mark for the thesis, the remaining 90% coming from the written thesis report.
The 30uoc coursework component of Quantitative Risk Honours will consist of five 6uoc lecture courses selected from the list below, or others, with the approval by the Head of School or nominee and taken with the advice of the honours thesis supervisor.
Approved Courses
- ACTL5301 Models for Risk Management (6 UOC)
- ACTL5302 Risk and Capital Management (6 UOC)
- ACTL5303 Asset-Liability Management (6 UOC)
- FINS4775 Research Methods in Finance 1 (6 UOC)
- FINS4776 Asset Pricing Theory (6 UOC)
- FINS4779 Research Methods in Finance 2 (6 UOC)
- MATH5335 Comput'l Methods for Finance (6 UOC)
- MATH5816 Continuous Time Fin'l Model'g (6 UOC)
- MATH5825 Measure, Integ & Probability (6 UOC)
- MATH5835 Stochastic Processes (6 UOC)
- MATH5905 Statistical Inference (6 UOC)
- MATH5965 Discrete Time Fin'l Modelling (6 UOC)
- MATH5975 Intro to Stochastic Analysis (6 UOC)
- MATH5985 Term Structure Modelling (6 UOC)
Note: Enrolment in courses outside the School of Mathematics and Statistics may be subject to approval from the controlling School or Department.
Final Mark
The marks for the thesis and other honours courses will be combined to give a weighted average mark forming a final honours mark which will be used to decide the grade of honours the student will be awarded as follows:
- Honours class 1 -- final mark of 85 or over
- Honours class 2, Division 1 -- final mark from 75 to 84
- Honours class 2, Division 2 -- final mark from 65 to 74
- Honours class 3 -- final mark from 50 to 64
Each student completing honours will be given an official document from the School of MathsStats which will list the courses completed, marks or grades awarded as well as the title and supervisor(s) of the honours thesis.
Pathways
Students who successfully complete Mathematics, Statistics or QR Honours are qualified to continue further in their research careers by applying to undertake postgraduate studies by PhD or Masters.
Students with successful honours are qualified to enrol in a PhD program at UNSW.
Students achieving a high Honours Grade (Class 1 or 2.1) may apply for an Australian Postgraduate Award (APA) PhD scholarship to support such studies. Further information can be obtained from MathsStats postgraduate studies webpages:
http://www.maths.unsw.edu.au/futurestudents/postgraduate-coursework
http://www.maths.unsw.edu.au/futurestudents/postgraduate-research
Graduates of a QR honours plan are also well qualified to find employment in many sectors, but typically in the banking or finance sector. Past honours graduates in other maths and stats honours programs have found employment in areas such as banking, computing, education, finance, government, medical research and meteorology. The Australian Mathematical Society and Australian Mathematical Sciences Institute maintain up-to-date information on career prospects in mathematics and statistics.
Students with successful honours are qualified to enrol in a PhD program at UNSW.
Students achieving a high Honours Grade (Class 1 or 2.1) may apply for an Australian Postgraduate Award (APA) PhD scholarship to support such studies. Further information can be obtained from MathsStats postgraduate studies webpages:
http://www.maths.unsw.edu.au/futurestudents/postgraduate-coursework
http://www.maths.unsw.edu.au/futurestudents/postgraduate-research
Graduates of a QR honours plan are also well qualified to find employment in many sectors, but typically in the banking or finance sector. Past honours graduates in other maths and stats honours programs have found employment in areas such as banking, computing, education, finance, government, medical research and meteorology. The Australian Mathematical Society and Australian Mathematical Sciences Institute maintain up-to-date information on career prospects in mathematics and statistics.
