detail

  • detail

MSc Quantitative Finance

Academic Year 2017/18

A programme specification is required for any programme on which a student may be registered. All programmes of the University are subject to the University's Quality Assurance and Enhancement processes as set out in the DASA Policies and Procedures Manual.

Programme Title

MSc Quantitative Finance

Final Award
(exit route if applicable for Postgraduate Taught Programmes)

Master of Science

Programme Code

FIN-MSC-QF

UCAS Code

JACS Code

N390 (DESCR) 100

Criteria for Admissions

Candidates will normally be expected to have an undergraduate honours degree, the equivalent of a UK Honours degree, upper second class, in Mathematics, Science, Engineering, Finance, Economics or other relevant quantitative subject, from a suitably quality assured university

We welcome applications from a diverse range of candidates so will also consider previous work experience alongside academic qualifications. We encourage candidates to submit a detailed CV. Candidates who lack the prerequisite academic qualification or equivalent may be required to attend an interview.

Additional Information for International Students
International applicants will be required to demonstrate evidence of language proficiency by one of the following:-
• An IELTS score of 6.5 with not less than 5.5 in each of the four component elements of listening, reading, speaking and writing taken within the last 2 years
• A TOEFL score of 90+ (internet based is the only acceptable form of this test); with at least the following scores in each of the four component parts of listening (17), reading (18), speaking (20) and writing (17) taken within the last 2 years.
• A first or good second class honours degree from a university based in the UK, Republic of Ireland or other suitably quality assured location where the medium of instruction is English
• A language assessment conducted by Queen’s University Belfast or approved provider
An alternative English Language qualification recognised by Queen’s University Belfast.
For Further Information refer to:
Further Information on academic staff, research interests, student support and teaching and learning initiatives for Queen’s University Management School can be found at www.qub.ac.uk/mgt

ATAS Clearance Required

No

Health Check Required

No

Portfolio Required

Interview Required

Mode of Study

Full Time

Type of Programme

Postgraduate

Length of Programme

1 Academic Year(s)

Total Credits for Programme

180

Exit Awards available

INSTITUTE INFORMATION

Awarding Institution/Body

Queen's University Belfast

Teaching Institution

Queen's University Belfast

School/Department

Queen's Management School

Framework for Higher Education Qualification Level 
http://www.qaa.ac.uk/publications/information-and-guidance

Level 7

QAA Benchmark Group
http://www.qaa.ac.uk/assuring-standards-and-quality/the-quality-code/subject-benchmark-statements

Business and Management (2015)

Accreditations (PSRB)

External Examiner Name:

External Examiner Institution/Organisation

Professor Gerhard Kling

University of London

REGULATION INFORMATION

Does the Programme have any approved exemptions from the University General Regulations
(Please see General Regulations)

No

Programme Specific Regulations

The MSc Quantitative Finance is based on the University wide modular framework. The class of degree awarded to the student (Fail, Pass, Commendation and Distinction) is based on a student’s performance in 8 modules plus the. Module marks are combined over the first and second semesters that together with the dissertation and are used to produce an aggregate mark. Marking is based on University agreed marking scale.


Level Information

Candidates will be assessed by coursework, class tests and a dissertation.

Students with protected characteristics

N/A

Are students subject to Fitness to Practise Regulations

(Please see General Regulations)

No

EDUCATIONAL AIMS OF PROGRAMME

The MSc in Computational Finance and Trading aims to:

provide effective systems of learning, academic guidance and pastoral support to encourage the academic, intellectual and personal development of our students;

(ii) provide students with the opportunity to pursue appropriately demanding programmes of study focused on asset pricing, quantitative finance, research methods in finance, numerical methods, trading and portfolio management, the pricing of derivatives and market microstructure;

develop students’ knowledge and skills base in ways which inter alia will enhance their employment opportunities;

maintain a supportive working environment in which there is respect for social and cultural differences and openness, fairness, and equality of opportunity in relation to selection, learning assessment and support

LEARNING OUTCOMES

Learning Outcomes: Cognitive Skills

On the completion of this course successful students will be able to:

Problem solving

Teaching/Learning Methods and Strategies

Cognitive skills are developed across the modules within the degree programme. The numerical and statistical components of the modules focus particularly on problem solving, logical reasoning and data management and analysis using statistical packages. Independent enquiry, critical evaluation and interpretation, abstraction and assimilation are key elements in all modules. Self-assessment and reflection are developed by formative feedback particularly on tutorial presentations and within the group work assignments.

Methods of Assessment

Assessment of cognitive skills, both summative and formative, occurs in the form of course homework, oral presentations, project work and class tests.

Logical reasoning

Teaching/Learning Methods and Strategies

Cognitive skills are developed across the modules within the degree programme. The numerical and statistical components of the modules focus particularly on problem solving, logical reasoning and data management and analysis using statistical packages. Independent enquiry, critical evaluation and interpretation, abstraction and assimilation are key elements in all modules. Self-assessment and reflection are developed by formative feedback particularly on tutorial presentations and within the group work assignments.

Methods of Assessment

Assessment of cognitive skills, both summative and formative, occurs in the form of course homework, oral presentations, project work and examinations.

Independent enquiry

Teaching/Learning Methods and Strategies

Cognitive skills are developed across the modules within the degree programme. The numerical and statistical components of the modules focus particularly on problem solving, logical reasoning and data management and analysis using statistical packages. Independent enquiry, critical evaluation and interpretation, abstraction and assimilation are key elements in all modules. Self-assessment and reflection are developed by formative feedback particularly on tutorial presentations and within the group work assignments.

Methods of Assessment

Assessment of cognitive skills, both summative and formative, occurs in the form of course homework, oral presentations, project work and examinations.

Critical evaluation and interpretation

Teaching/Learning Methods and Strategies

Cognitive skills are developed across the modules within the degree programme. The numerical and statistical components of the modules focus particularly on problem solving, logical reasoning and data management and analysis using statistical packages. Independent enquiry, critical evaluation and interpretation, abstraction and assimilation are key elements in all modules. Self-assessment and reflection are developed by formative feedback particularly on tutorial presentations and within the group work assignments.

Methods of Assessment

Assessment of cognitive skills, both summative and formative, occurs in the form of course homework, oral presentations, project work and examinations.

Self assessment and reflection

Teaching/Learning Methods and Strategies

Cognitive skills are developed across the modules within the degree programme. The numerical and statistical components of the modules focus particularly on problem solving, logical reasoning and data management and analysis using statistical packages. Independent enquiry, critical evaluation and interpretation, abstraction and assimilation are key elements in all modules. Self-assessment and reflection are developed by formative feedback particularly on tutorial presentations and within the group work assignments.

Methods of Assessment

Assessment of cognitive skills, both summative and formative, occurs in the form of course homework, oral presentations, project work and examinations.

Learning Outcomes: Transferable Skills

On the completion of this course successful students will be able to:

The ability to synthesise information/data from variety of sources including from databases, books, journal articles and the internet

Teaching/Learning Methods and Strategies

Transferable skills development will permeate the teaching and learning on the degree programme. Successful completion of coursework requires students to gather information from a range of sources, select and assimilate relevant information and to complete tasks within deadlines.

Methods of Assessment

Assessment of coursework requires students to use a range of media (e.g., worked solutions and proofs, essays, Powerpoint presentations, statistical based project work) to demonstrate their learning. Completion of the dissertation develops skills in independent research enquiry, data analysis and presentation.

The preparation and communication of ideas in finance, information economics, quantitative finance, and trading in both written and presentational forms

Teaching/Learning Methods and Strategies

Transferable skills development will permeate the teaching and learning on the degree programme. Successful completion of coursework requires students to gather information from a range of sources, select and assimilate relevant information and to complete tasks within deadlines.

Methods of Assessment

Assessment of coursework requires students to use a range of media (e.g., worked solutions and proofs, essays, Powerpoint presentations, statistical based project work) to demonstrate their learning. Completion of the dissertation develops skills in independent research enquiry, data analysis and presentation.

The ability to work both independently and in groups

Teaching/Learning Methods and Strategies

Transferable skills development will permeate the teaching and learning on the degree programme. Successful completion of coursework requires students to gather information from a range of sources, select and assimilate relevant information and to complete tasks within deadlines.

Methods of Assessment

Assessment of coursework requires students to use a range of media (e.g., worked solutions and proofs, essays, Powerpoint presentations, statistical based project work) to demonstrate their learning. Completion of the dissertation develops skills in independent research enquiry, data analysis and presentation.

Organisation and time management

Teaching/Learning Methods and Strategies

Transferable skills development will permeate the teaching and learning on the degree programme. Successful completion of coursework requires students to gather information from a range of sources, select and assimilate relevant information and to complete tasks within deadlines.

Methods of Assessment

Assessment of coursework requires students to use a range of media (e.g., worked solutions and proofs, essays, Powerpoint presentations, statistical based project work) to demonstrate their learning. Completion of the dissertation develops skills in independent research enquiry, data analysis and presentation.

Problem solving and critical analysis

Teaching/Learning Methods and Strategies

Transferable skills development will permeate the teaching and learning on the degree programme. Successful completion of coursework requires students to gather information from a range of sources, select and assimilate relevant information and to complete tasks within deadlines.

Methods of Assessment

Assessment of coursework requires students to use a range of media (e.g., worked solutions and proofs, essays, Powerpoint presentations, statistical based project work) to demonstrate their learning. Completion of the dissertation develops skills in independent research enquiry, data analysis and presentation.

Work-based skills; use of IT, including word-processing, email, internet and statistical/econometric/risk management packages

Teaching/Learning Methods and Strategies

Transferable skills development will permeate the teaching and learning on the degree programme. Successful completion of coursework requires students to gather information from a range of sources, select and assimilate relevant information and to complete tasks within deadlines.

Methods of Assessment

Assessment of coursework requires students to use a range of media (e.g., worked solutions and proofs, essays, Powerpoint presentations, statistical based project work) to demonstrate their learning. Completion of the dissertation develops skills in independent research enquiry, data analysis and presentation.

The ability to communicate quantitative and qualitative information together with analysis, argument and commentary in a form appropriate to different intended audiences

Teaching/Learning Methods and Strategies

Transferable skills development will permeate the teaching and learning on the degree programme. Successful completion of coursework requires students to gather information from a range of sources, select and assimilate relevant information and to complete tasks within deadlines.

Methods of Assessment

Assessment of coursework requires students to use a range of media (e.g., worked solutions and proofs, essays, Powerpoint presentations, statistical based project work) to demonstrate their learning. Completion of the dissertation develops skills in independent research enquiry, data analysis and presentation.

Learning Outcomes: Knowledge & Understanding

On the completion of this course successful students will be able to:

The theoretical and conceptual underpinnings of finance, information economics, and market structure

Teaching/Learning Methods and Strategies

The MSc in Quantitative Finance follows a structured curriculum based upon modules in asset pricing, trading and portfolio management, research methods in finance, computational methods, market microstructure, the pricing of derivatives and time-series financial econometrics.

Acquisition of knowledge and understanding is through structured exposition based on lectures, directed reading of academic journals which are particularly applied to student presentations and group projects, tutorials, computer-based laboratory work, group work, and private study.

Methods of Assessment

Class tests, individual and group projects, take-home tests, individual and group oral presentations and case study investigations are used to assess student learning.

The fundamental principles of stochastic processes in finance and risk analysis

Teaching/Learning Methods and Strategies

The MSc in Quantitative Finance follows a structured curriculum based upon modules in asset pricing, trading and portfolio management, research methods in finance, computational methods, market microstructure, the pricing of derivatives and time-series financial econometrics.

Acquisition of knowledge and understanding is through structured exposition based on lectures, directed reading of academic journals which are particularly applied to student presentations and group projects, tutorials, computer-based laboratory work, group work, and private study.

Methods of Assessment

Class tests, individual and group projects, take-home tests, individual and group oral presentations and case study investigations are used to assess student learning.

The evaluation and assessment of different types of financial risk

Teaching/Learning Methods and Strategies

The MSc in Quantitative Finance follows a structured curriculum based upon modules in asset pricing, trading and portfolio management, research methods in finance, computational methods, market microstructure, the pricing of derivatives and time-series financial econometrics.

Acquisition of knowledge and understanding is through structured exposition based on lectures, directed reading of academic journals which are particularly applied to student presentations and group projects, tutorials, computer-based laboratory work, group work, and private study.

Methods of Assessment

Class tests, individual and group projects, take-home tests, individual and group oral presentations and case study investigations are used to assess student learning.

The evaluation, assessment and use of financial instruments to mitigate financial risk

Teaching/Learning Methods and Strategies

The MSc in Quantitative Finance follows a structured curriculum based upon modules in asset pricing, trading and portfolio management, research methods in finance, computational methods, market microstructure, the pricing of derivatives and time-series financial econometrics.

Acquisition of knowledge and understanding is through structured exposition based on lectures, directed reading of academic journals which are particularly applied to student presentations and group projects, tutorials, computer-based laboratory work, group work, and private study.

Methods of Assessment

Class tests, individual and group projects, take-home tests, individual and group oral presentations and case study investigations are used to assess student learning.

The principles of asset pricing

Teaching/Learning Methods and Strategies

The MSc in Quantitative Finance follows a structured curriculum based upon modules in asset pricing, trading and portfolio management, research methods in finance, computational methods, market microstructure, the pricing of derivatives and time-series financial econometrics.

Acquisition of knowledge and understanding is through structured exposition based on lectures, directed reading of academic journals which are particularly applied to student presentations and group projects, tutorials, computer-based laboratory work, group work, and private study.

Methods of Assessment

Class tests, individual and group projects, take-home tests, individual and group oral presentations and case study investigations are used to assess student learning.

The relevant computational, quantitative and statistical techniques

Teaching/Learning Methods and Strategies

The MSc in Quantitative Finance follows a structured curriculum based upon modules in asset pricing, trading and portfolio management, research methods in finance, computational methods, market microstructure, the pricing of derivatives and time-series financial econometrics.

Acquisition of knowledge and understanding is through structured exposition based on lectures, directed reading of academic journals which are particularly applied to student presentations and group projects, tutorials, computer-based laboratory work, group work, and private study.

Methods of Assessment

Class tests, individual and group projects, take-home tests, individual and group oral presentations and case study investigations are used to assess student learning.

The key principles of trading

Teaching/Learning Methods and Strategies

The MSc in Quantitative Finance follows a structured curriculum based upon modules in asset pricing, trading and portfolio management, research methods in finance, computational methods, market microstructure, the pricing of derivatives and time-series financial econometrics.

Acquisition of knowledge and understanding is through structured exposition based on lectures, directed reading of academic journals which are particularly applied to student presentations and group projects, tutorials, computer-based laboratory work, group work, and private study.

Methods of Assessment

Class tests, individual and group projects, take-home tests, individual and group oral presentations and case study investigations are used to assess student learning.

Learning Outcomes: Subject Specific

On the completion of this course successful students will be able to:

The ability to construct arguments and exercise problem solving skills in the context of theories of finance and risk management

Teaching/Learning Methods and Strategies

Mathematical skills, through problem solving, and computer application, are at the core of the work undertaken by a specialist in Quantitative Finance. Consequently, these are core elements in each semester of the degree and are built upon across modules and throughout the course of the programme. The economic and financial environment both influences and generates the work in which risk specialists are involved and therefore in these areas problem solving, data analysis and computer application skills are developed and built upon across modules. In addition, in the modules in these two areas, up-to-date finance, economic and risk related literature is integrated into the curriculum, with an important element being the ongoing development of the students’ ability to communicate, debate and critique this literature.

Methods of Assessment

Both summative and formative assessment methods are used throughout all modules.

Formative assessment takes two main forms. First, weekly homework is aimed at promoting understanding, logic and accurate calculation. Secondly, weekly discussion of key theories and academic readings to develop understanding, logical argument and critical assessment.

Summative assessment also takes a variety of forms. In all modules end-of-term class tests are used to gauge and assess understanding and the acquisition of knowledge. Cumulative assessment is also built into all modules to assess ongoing understanding. A variety of forms of cumulative assessment is employed:-

(i) practical trading-room-based work in a range of modules;

(ii) a mixture of class tests, group and individual presentations, essays and case investigations in the microstructure and stochastic processes modules.

The ability to use computer-based mathematical / statistical / econometric packages to analyse and evaluate relevant data

Teaching/Learning Methods and Strategies

Mathematical skills, through problem solving, and computer application, are at the core of the work undertaken by a specialist in Quantitative Finance. Consequently, these are core elements in each semester of the degree and are built upon across modules and throughout the course of the programme. The economic and financial environment both influences and generates the work in which risk specialists are involved and therefore in these areas problem solving, data analysis and computer application skills are developed and built upon across modules. In addition, in the modules in these two areas, up-to-date finance, economic and risk related literature is integrated into the curriculum, with an important element being the ongoing development of the students’ ability to communicate, debate and critique this literature.

Methods of Assessment

Both summative and formative assessment methods are used throughout all modules.

Formative assessment takes two main forms. First, weekly homework is aimed at promoting understanding, logic and accurate calculation. Secondly, weekly discussion of key theories and academic readings to develop understanding, logical argument and critical assessment.

Summative assessment also takes a variety of forms. In all modules end-of-term class tests are used to gauge and assess understanding and the acquisition of knowledge. Cumulative assessment is also built into all modules to assess ongoing understanding. A variety of forms of cumulative assessment is employed:-

(i) practical trading-room-based work in a range of modules;

(ii) a mixture of class tests, group and individual presentations, essays and case investigations in the microstructure and stochastic processes modules.

The ability to read and evaluate finance academic literature

Teaching/Learning Methods and Strategies

Mathematical skills, through problem solving, and computer application, are at the core of the work undertaken by a specialist in Quantitative Finance. Consequently, these are core elements in each semester of the degree and are built upon across modules and throughout the course of the programme. The economic and financial environment both influences and generates the work in which risk specialists are involved and therefore in these areas problem solving, data analysis and computer application skills are developed and built upon across modules. In addition, in the modules in these two areas, up-to-date finance, economic and risk related literature is integrated into the curriculum, with an important element being the ongoing development of the students’ ability to communicate, debate and critique this literature.

Methods of Assessment

Both summative and formative assessment methods are used throughout all modules.

Formative assessment takes two main forms. First, weekly homework is aimed at promoting understanding, logic and accurate calculation. Secondly, weekly discussion of key theories and academic readings to develop understanding, logical argument and critical assessment.

Summative assessment also takes a variety of forms. In all modules end-of-term class tests are used to gauge and assess understanding and the acquisition of knowledge. Cumulative assessment is also built into all modules to assess ongoing understanding. A variety of forms of cumulative assessment is employed:-

(i) practical trading-room-based work in a range of modules;

(ii) a mixture of class tests, group and individual presentations, essays and case investigations in the microstructure and stochastic processes modules.

The ability to appreciate, construct and analyse mathematical, statistical, financial and economic models of trading

Teaching/Learning Methods and Strategies

Mathematical skills, through problem solving, and computer application, are at the core of the work undertaken by a specialist in Quantitative Finance. Consequently, these are core elements in each semester of the degree and are built upon across modules and throughout the course of the programme. The economic and financial environment both influences and generates the work in which risk specialists are involved and therefore in these areas problem solving, data analysis and computer application skills are developed and built upon across modules. In addition, in the modules in these two areas, up-to-date finance, economic and risk related literature is integrated into the curriculum, with an important element being the ongoing development of the students’ ability to communicate, debate and critique this literature.

Methods of Assessment

Both summative and formative assessment methods are used throughout all modules.

Formative assessment takes two main forms. First, weekly homework is aimed at promoting understanding, logic and accurate calculation. Secondly, weekly discussion of key theories and academic readings to develop understanding, logical argument and critical assessment.

Summative assessment also takes a variety of forms. In all modules end-of-term class tests are used to gauge and assess understanding and the acquisition of knowledge. Cumulative assessment is also built into all modules to assess ongoing understanding. A variety of forms of cumulative assessment is employed:-

(i) practical trading-room-based work in a range of modules;

(ii) a mixture of class tests, group and individual presentations, essays and case investigations in the microstructure and stochastic processes modules.

The ability to understand the principles of computer programming and use Matlab

Teaching/Learning Methods and Strategies

Mathematical skills, through problem solving, and computer application, are at the core of the work undertaken by a specialist in Quantitative Finance. Consequently, these are core elements in each semester of the degree and are built upon across modules and throughout the course of the programme. The economic and financial environment both influences and generates the work in which risk specialists are involved and therefore in these areas problem solving, data analysis and computer application skills are developed and built upon across modules. In addition, in the modules in these two areas, up-to-date finance, economic and risk related literature is integrated into the curriculum, with an important element being the ongoing development of the students’ ability to communicate, debate and critique this literature.

Methods of Assessment

Both summative and formative assessment methods are used throughout all modules.

Formative assessment takes two main forms. First, weekly homework is aimed at promoting understanding, logic and accurate calculation. Secondly, weekly discussion of key theories and academic readings to develop understanding, logical argument and critical assessment.

Summative assessment also takes a variety of forms. In all modules end-of-term class tests are used to gauge and assess understanding and the acquisition of knowledge. Cumulative assessment is also built into all modules to assess ongoing understanding. A variety of forms of cumulative assessment is employed:-

(i) practical trading-room-based work in a range of modules;

(ii) a mixture of class tests, group and individual presentations, essays and case investigations in the microstructure and stochastic processes modules.

The ability to use the trading room and the Bloomberg database

Teaching/Learning Methods and Strategies

Mathematical skills, through problem solving, and computer application, are at the core of the work undertaken by a specialist in Quantitative Finance. Consequently, these are core elements in each semester of the degree and are built upon across modules and throughout the course of the programme. The economic and financial environment both influences and generates the work in which risk specialists are involved and therefore in these areas problem solving, data analysis and computer application skills are developed and built upon across modules. In addition, in the modules in these two areas, up-to-date finance, economic and risk related literature is integrated into the curriculum, with an important element being the ongoing development of the students’ ability to communicate, debate and critique this literature.

Methods of Assessment

Both summative and formative assessment methods are used throughout all modules.

Formative assessment takes two main forms. First, weekly homework is aimed at promoting understanding, logic and accurate calculation. Secondly, weekly discussion of key theories and academic readings to develop understanding, logical argument and critical assessment.

Summative assessment also takes a variety of forms. In all modules end-of-term class tests are used to gauge and assess understanding and the acquisition of knowledge. Cumulative assessment is also built into all modules to assess ongoing understanding. A variety of forms of cumulative assessment is employed:-

(i) practical trading-room-based work in a range of modules;

(ii) a mixture of class tests, group and individual presentations, essays and case investigations in the microstructure and stochastic processes modules.

MODULE INFORMATION

Programme Requirements

Module Title

Module Code

Level/ stage

Credits

Availability

Duration

Pre-requisite

 

Assessment

 

 

 

 

S1

S2

 

 

Core

Option

Coursework %

Practical %

Examination %

Derivatives

FIN9007

7

15

YES

10 weeks

N

YES

40%

60%

0%

Corporate Finance

FIN9005

7

15

YES

9 weeks

N

YES

40%

60%

0%

Research Methods in Finance

FIN9008

7

15

YES

9 weeks

N

YES

30%

70%

0%

Asset Pricing

FIN7026

7

15

YES

9 weeks

N

YES

40%

60%

0%

Market Microstructure

FIN7027

7

15

YES

9 weeks

N

YES

40%

60%

0%

Times-Series Financial Econometrics

FIN7028

7

15

YES

10 weeks

N

YES

30%

70%

0%

Computational Methods in Finance

FIN7029

7

15

YES

10 weeks

N

YES

40%

60%

0%

Trading Principles

FIN7030

7

15

YES

10 weeks

N

YES

50%

50%

0%

Dissertation- Msc Quantitative Finance

FIN9099

7

60

14 weeks

N

YES

100%

0%

0%

Notes