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2023/24 Taught Postgraduate Programme Catalogue

MSc Statistics with Applications to Finance

Programme code:MSC-STAT/FINUCAS code:
Duration:12 Months Method of Attendance: Full Time
Programme manager:Dr Luisa Cutillo Contact address:mscstats_dsa@leeds.ac.uk

Total credits: 180

Entry requirements:

BSc (or equivalent) in a subject containing a substantial mathematical and statistical component, usually at level 2.1 or above (or equivalent).

School/Unit responsible for the parenting of students and programme:

School of Mathematics

Examination board through which the programme will be considered:

School of Mathematics

Programme specification:

The programme will:
- provide a solid training in mainstream advanced statistical modelling with special focus on statistical finance
- expose students to modern developments in statistical finance
- reflect the research interests of the department in stochastic financial modelling.


At the end of the programme students should:
- be able to embark on a programme of research as a research student
- be able to undertake data analysis for a variety of statistical problems with special focus on financial data
- have learned key programming skills, both in data analysis and mathematical typesetting
- be equipped as a financial statistician for a range of careers in industry, commerce and the public sector
- have learned to express mathematical concepts and statistical analysis in both written and verbal form.


Year1 - View timetable

[Learning Outcomes, Transferable (Key) Skills, Assessment]

Candidates must enroll on exactly 180 or 185 credits overall, with at least 135 credits at level 5M. Please note that in order to obtain the MSc award students need to pass 150 credits with at least 135 at level 5 with a minimum classification average of 5.0 . Please refer to the 'rules of award' document for further details, with particular attention to section 16.

Students will be awarded the PGCert if they exit with 60 credits (including 45 at Level 5M), or the PGDip if they exit with 90 credits (including 75 at Level 5M).

Compulsory modules:

Candidates will be required to study the following compulsory modules:

MATH5320MDiscrete Time Finance15 creditsSemester 1 (Sep to Jan)
MATH5330MContinuous Time Finance15 creditsSemester 2 (Jan to Jun)
MATH5340MRisk Management15 creditsSemester 2 (Jan to Jun)
MATH5802MTime Series and Spectral Analysis15 creditsSemester 1 (Sep to Jan)
MATH5871MDissertation in Statistics60 credits1 Jun to 30 Sep

Optional modules:

Candidates will be required to study 60 to 65 credits from the following optional modules:

MATH3092Mixed Models10 creditsSemester 2 (Jan to Jun)
MATH3820Bayesian Statistics10 creditsNot running in 202324
MATH3823Generalised Linear Models10 creditsSemester 2 (Jan to Jun)
MATH5092MMixed Models with Medical Applications15 creditsSemester 2 (Jan to Jun)
MATH5306MIntroduction to Programming5 creditsSemester 1 (Sep to Jan)
MATH5350MComputations in Finance15 creditsSemester 2 (Jan to Jun)
MATH5714MLinear Regression, Robustness and Smoothing20 creditsSemester 1 (Sep to Jan)
MATH5772MMultivariate and Cluster Analysis15 creditsSemester 1 (Sep to Jan)
MATH5820MBayesian Statistics and Causality15 creditsNot running in 202324
MATH5824MGeneralised Linear and Additive Models15 creditsSemester 2 (Jan to Jun)
MATH5825MIndependent Learning and Skills Project15 creditsSemester 2 (Jan to Jun)
MATH5835MStatistical Computing15 creditsSemester 1 (Sep to Jan)

Last updated: 20/02/2024 15:58:00

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