Problem solve

Reason logically

Conduct independent enquiry

Critically evaluate and interpret

Self-assess and reflect

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/exams.

Organise and manage their time

Synthesise and evaluate information/data from a variety of sources including from databases, books, journal articles and the internet

Work both independently and in groups

Make effective use of information technology including relevant subject-specific packages

Communicate ideas in both written and presentational forms

Confidently engage with the world of practice

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.

Appreciate diversity and be capable of placing issues within their local and international contexts

Engage with issues around ethics, responsibility and sustainability

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

The fundamental principles of stochastic processes in finance and risk analysis

The evaluation and assessment of different types of financial risk

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

The principles of asset pricing

The relevant computational, quantitative and statistical techniques

The key principles of algorithmic trading and investment

Teaching/Learning Methods and Strategies

The MSc in Financial Analytics 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/exams, individual and group projects, take-home tests, individual and group oral presentations and case study investigations are used to assess student learning.

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

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

The ability to read and evaluate finance academic literature

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

The ability to understand the principles of computer programming.

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 Financial Analytics. 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.

Summative assessment also takes a variety of forms. Assessment is also built into all modules to assess ongoing understanding.