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MSc in Quantitative Methods for Risk Management

Programme Code: TMQMRM

Department: Statistics

For students starting this programme of study in 2022/23

Guidelines for interpreting programme regulations


Students take three compulsory half unit courses and 2.5 units of optional courses.

Students are required to take a two-week compulsory introductory course MA400 September Introductory Course (Financial Mathematics) in September.

Please note that places are limited on some optional courses. Admission onto any particular course is not guaranteed and may be subject to timetabling constraints and/or students meeting specific prerequisite requirements.

Paper

Course number, title (unit value)

Introductory Course

MA400 September Introductory Course (Financial Mathematics and Quantitative Methods for Risk Management) (0.0)

Paper 1

ST409 Stochastic Processes (0.5) #

Paper 2

ST429 Statistical Methods for Risk Management (0.5) #

Paper 3

ST433 Computational Methods in Finance and Insurance (0.5) #

Papers 4 & 5

Courses to the value of 1.5 unit(s) from the following:

 

MA411 Probability and Measure (0.5) #

 

MA415 The Mathematics of the Black and Scholes Theory (0.5) #

 

MA416 The Foundations of Interest Rate and Credit Risk Theory (0.5) #

 

MA420 Quantifying Risk and Modelling Alternative Markets (0.5) #  (not available 2022/23)

 

MA435 Machine Learning in Financial Mathematics (0.5) #

 

ST422 Time Series (0.5) #

 

ST426 Applied Stochastic Processes (0.5)

 

ST436 Financial Statistics (0.5) #

 

ST439 Stochastics for Derivatives Modelling (0.5) #

 

ST440 Recent Developments in Finance and Insurance (0.5) #

 

ST443 Machine Learning and Data Mining (0.5) #

 

ST446 Distributed Computing for Big Data (0.5) #

 

ST448 Insurance Risk (0.5) #

 

ST449 Artificial Intelligence (0.5)

 

ST451 Bayesian Machine Learning (0.5) #

 

ST455 Reinforcement Learning (0.5) #

 

ST456 Deep Learning (0.5) #

 

ST457 Graph Data Analytics and Representation Learning (0.5) #

Paper 6

Courses to the value of 1.0 unit(s) from the following:

 

FM441 Derivatives (0.5) #

 

FM442 Quantitative Methods for Finance and Risk Analysis (0.5) #

 

MA409 Continuous Time Optimisation (0.5) #

 

ST452 Probability and Mathematical Statistics I (0.5)

 

ST453 Probability and Mathematical Statistics II (0.5) #

 

Further half-units(s) from the Paper 5 options list, or from other appropriate MSc courses subject to the approval of the Programme Director and the teacher responsible for the course.

Papers 4 & 5 options list

Additional course 1

Students taking FM442 can apply for a place on the following non-assessed computer course:

 

FM457 Applied Computational Finance (0.0)  (not available 2022/23)

Additional course 2

Students can also take the following non-assessed course taken in addition to the required five compulsory half unit courses and three half units of optional courses detailed above:

 

MA422 Research Topics in Financial Mathematics (0.0)

Papers 4 & 5 options list

MA411 Probability and Measure (0.5) #

MA415 The Mathematics of the Black and Scholes Theory (0.5) #

MA416 The Foundations of Interest Rate and Credit Risk Theory (0.5) #

MA420 Quantifying Risk and Modelling Alternative Markets (0.5) #  (not available 2022/23)

MA435 Machine Learning in Financial Mathematics (0.5) #

ST422 Time Series (0.5) #

ST426 Applied Stochastic Processes (0.5)

ST436 Financial Statistics (0.5) #

ST439 Stochastics for Derivatives Modelling (0.5) #

ST440 Recent Developments in Finance and Insurance (0.5) #

ST443 Machine Learning and Data Mining (0.5) #

ST446 Distributed Computing for Big Data (0.5) #

ST448 Insurance Risk (0.5) #

ST449 Artificial Intelligence (0.5)

ST451 Bayesian Machine Learning (0.5) #

ST455 Reinforcement Learning (0.5) #

ST456 Deep Learning (0.5) #

ST457 Graph Data Analytics and Representation Learning (0.5) #


# means there may be prerequisites for this course. Please view the course guide for more information.

The  facilitates comparability and compatibility between higher education systems across the European Higher Education Area. Some of the School's taught master's programmes are nine or ten months in duration. If you wish to proceed from these programmes to higher study in EHEA countries other than the UK, you should be aware that their recognition for such purposes is not guaranteed, due to the way in which ECTS credits are calculated.

Note for prospective students:
For changes to graduate course and programme information for the next academic session, please see the . Changes to course and programme information for future academic sessions can be found on the .