MSc Statistics and Computational Finance Programme Specification 2024-25

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1	ACADEMIC QUALITY TEAM
2	Programme Specifications 2024-25
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5	Programme Title			MSc Statistics and Computational Finance
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7	This document applies to students who commenced the programme(s) in:			2024			Award type			MSc
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9	What level is this qualification?			Level 7			Length of programme			1 year
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11	Mode of study (Full / Part Time)			Full-time
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13	Will the programme use standard University semester dates?			Yes			For York Online programmes, will standard dates for such programmes be used?			N/A
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15	Awarding institution			University of York			Board of Studies for the programme			Mathematics
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17	Lead department			Mathematics			Other contributing departments			N/A
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19	Language of study and assessment			English			Language(s) of assessment			English
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21	Is this a campus-based or online programme?			Campus-based
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23	Partner organisations
24	If there are any partner organisations involved in the delivery of the programme, please outline the nature of their involvement. You may wish to refer to the Policy on Collaborative Provision
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26	N/A
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28	Reference points
29	Please state relevant reference points consulted in the design of this programme (for example, relevant documentation setting out PSRB requirements; the University's Frameworks for Programme Design (UG or PGT); QAA Subject Benchmark Statements; QAA Qualifications and Credit Frameworks).
30	Taught Postgraduate Programme Design Policy ; QAA Subject Benchmark Statement: Mathematics, Statistics and Operational Research.
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33	Credit Transfer and Recognition of Prior Learning
34	Will this programme involve any exemptions from the University Policy and Procedures on Credit Transfer and the Recognition of Prior Learning? If so, please specify and give a rationale
35	No exemptions
36	No exemptions
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38	Exceptions to Regulations
39	Please detail any exceptions to University Award Regulations and Frameworks that need to be approved (or are already approved) for this programme. This should include any that have been approved for related programmes and should be extended to this programme.
40	No exemptions
41	No exemptions
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43	Internal Transfers
44	Please use the boxes below to specify if transfers into / out of the programme from / to other programmes within the University are possible by indicating yes or no and listing any restrictions. These boxes can also be used to highlight any common transfer routes which it would be useful for students to know.
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46		Transfers in:	Not possible				Transfers out:	Not possible
47			Not possible					Not possible
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49	Statement of Purpose
50	Please briefly outline the overall aims of the programme. This should clarify to a prospective student why they should choose this programme, what it will provide to them and what benefits they will gain from completing it.
51	This one-year taught Masters programme trains graduates to work as professional data scientists/ financial analysts at the interface between statistics and finance. In a nutshell, this programme will equip you with the necessary skills to (i) 'translate' problems from the applied workplace into the appropriate contemporary statistical ideas and methodologies, (ii) use your advanced knowledge in statistical modelling and computational finance to provide solutions to these problems, and (iii) interpret and communicate your results. You will be taught by a team who produces world-class research and will have full access to this expertise. Our MSc degree in Statistics and Computational Finance equips graduates with big data analysis skills, including the computational transferable skills required by finance-based employers, and provides attractive employment opportunities in a growing number of industries, e.g. finance, government, consultancy and research. Students with interest in academic work may also decide to continue on a PhD programme in Statistics or a related field, for which this MSc programme provides a sound foundation.
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59	If there are additional awards associated with the programme upon which students can register, please specify the Statement of Purpose for that programme. This will be most relevant for PGT programmes with exit awards that are also available as entry points. Use additional rows to include more than one additional award. Do not include years in industry / abroad (for which there are separate boxes).
60	Exit Award Title			Is the exit award also available as an entry point?	Outcomes: what will the student be able to do on exit with this award?				Specify the module diet that the student will need to complete to obtain this exit award
61	Postgraduate Certificate in Statistics and Computational Finance			Exit award only	N/A				Any 60 credits from the taught phase
62	Postgraduate Diploma in Statistics and Computtional Finance			Exit award only	N/A				Complete the Taught Phase (all 120 credits)
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64	Programme Learning Outcomes
65	What are the programme learning outcomes (PLOs) for the programme? (Normally a minimum of 6, maximum of 8). Taken together, these outcomes should capture the distinctive features of the programme and represent the outcomes that students progressively develop in the programme and achieve at graduation. PLOs should be worded to follow the stem 'Graduates will be able to...'
66	1	Use, with a high level of confidence and sophistication, the appropriate modern statistical (incl. probabilistic) methodology and associated tools that underpin a wide range of applied problems, particularly in finance, big data analysis but also more generally in science and industry.
67	2	Recognise and critically evaluate different statistical (incl. probabilistic) methods in order to find a suitable strategy for solving an unfamiliar problem open to investigation.
68	3	Use logical reasoning as a basis for the critical analysis of ideas or statements which have a statistical and financial context, and develop independently their own ideas using well-founded reasoning.
69	4	Independently conduct a piece of applied research in a relevant specialised area, for example take into account recent statistical methodology, apply it and interpret conclusions on real data sources.
70	5	Communicate advanced statistical and mathematical analyses and associated conclusions clearly, in writing or in a presentation, at a level appropriate for the intended audience.
71	6	Create mathematical documents, presentations and computer programmes by accurately and efficiently using a range of digital technologies and programming tools.
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73	Diverse entry routes
74	Detail how you would support students from diverse entry routes to transition into the programme. For example, disciplinary knowledge and conventions of the discipline, language skills, academic and writing skills, lab skills, academic integrity.
75	The role of the personal tutor is to recognize the needs of students when they arrive in the first year and signpost them to appropriate support services. We also advise the students to use the support of the Writing Centre, which offers advice and guidance on academic writing, critical thinking and analysis skills, developing effective study habits and communication skills.
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79	Inclusion
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81	Please confirm by ticking the box on the right that the design, content and delivery of the programme will support students from all backgrounds to succeed. This refers to the University's duties under the Equality Act 2010. You may wish to refer to the optional Inclusive Learning self-assessment tools to support reflection on this issue.										TRUE
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83	Employability
84	Please give a brief overview - no more than 5 sentences - of how the programmes helps develop students' employability. Your Faculty Employability Manager can help reflection on this issue. This statement will be used by Marketing as the basis for external content with respect to employability.
85	Our Mathematics modules teach research skills, precise logical thinking, problem analysis, and intellectual communication. These skills are required in a wide range of sectors and our former students have been successful in securing jobs in companies, governmental agencies, and academia. We will help you identify and reflect on the professional skills gained and personal strengths developed from your course and clearly articulate how these can be transferred to a work context.
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91	[For Undergraduate and Integrated Masters Programmes Only]
92	Are you offering any variations of this programme, such as additional years abroad or industry?
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94	Year abroad			FALSE		Will the year abroad programme be available directly via UCAS; for students to transfer in having entered the main programme; or both?				MSc programme, not UG
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96	Year in industry			FALSE		Will the year in industry programme be available directly via UCAS; for students to transfer in having entered the main programme; or both?				MSc programme, not UG
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98	Year in enterprise			FALSE
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100	Placement year			FALSE