MSc Investment Management

The MSc Investment Management programe can be studied full time (over one year) or part time (over two years). The programme will consist of four core, three optional modules and a dissertation. The core Investment Analysis and Management module will be worth 30 credits and will be taught over the full academic year while the other six modules are worth 15 credits and taught are taught throughout the programme.

The dissertation carries 60 credits. Taught modules will contain a mix of assessment components, both summative and formative. These might include in-class tests, computer based assignments, essays, case studies, group presentations and assignments and examinations.

You will be able to tailor your learning to your career goals. Core modules are offered on investment analysis and the main financial instruments, trading strategies and risk management of investment funds. Optional modules are offered in accounting and corporate finance, structured derivative products, quantitative methods and computational tools.

• • Investment Analysis and Management (30 Credits) - Compulsory This module provides participants with a sound grounding in the theory and practice of investment analysis and management. Specific aims include: equity analysis, generating investment ideas, estimating investment risk & returns and the use of derivative instruments. Students are exposed to the key concepts and tools involved and further asked to apply them to analyse real life financial assets.
  • Corporate Finance and Valuation (15 Credits) - Compulsory Develops understanding of the major issues in corporate finance and the acquisition of valuation skills. In particular it develops the students’ ability to critically analyse risk, return and growth expectation of earnings and cash flows to the companies and financial assets while applying the various valuation tools and techniques to live cases.
  • Fixed-Income Securities (15 Credits) - Compulsory The aim of this module is to deepen students’ knowledge of fixed income products. The module will also incorporate new developments in fixed-income derivatives such as mortgage-backed securities, collateralised debt obligations and other structured fixed-income financial products.
  • Applied Econometrics (15 Credits) - Compulsory Deals with basic statistical methods and explores the application of these methods to analytical models in finance. The aim is to provide students with the analytical and programming skills necessary to pursue empirical studies in finance. The students are encouraged to use previous knowledge in statistics and computer programming.
  • Research Methods and Dissertation (60 Credits) - Compulsory Provides students with the opportunity to select their own specialised research topic in the area of financial management. Students will be expected to apply relevant theoretical frameworks, the existing seminal and the most up-to-date scholarly literature together with the relevant research methodologies while conducting their research. The module requires students to independently plan, organise and coherently produce a limited but well researched work.
  • Corporate Governance and Accountability (15 Credits) - Optional

    Examines the evolution of corporate governance and accountability mechanisms from theoretical and practical viewpoints. Topical issues in corporate governance and social reporting, such as high profile cases of corporate failure, are critically discussed to elevate students’ understanding of how such mechanisms can be applied to enhance corporate accountability.

  • Financial Reporting (15 Credits) - Optional This module aims to provide a critical understanding of the financial accounting techniques and practices and their relevance to contemporary business. The impact of international regulatory frameworks on these practices will be evaluated.
  • Entrepreneurial Finance (15 Credits) - Optional

    The module aims to provide students with an awareness and understanding of the mechanics, challenges and issues related to the different ways of financing an enterprise.

  • Financial Data and Computing (15 Credits) - Optional Deals with information and communication technology to carry out financial analysis in detail. Students will be able to learn skills and ideas to implement computational approaches towards financial problems. Students will be able to handle, manage and analyse financial data using Visual Basic and Excel.
  • Risk Measurement (15 Credits) - Optional Aims to introduce students to concepts of risk measurement and analysis of financial data. The module provides knowledge and basic skills required for risk measurement, technical analysis of financial data, investment decision-making, portfolio selection and optimisation. The students are expected to have basic knowledge of probability theory and statistics at undergraduate level.
  • Managerial Accounting (15 Credits) - Optional Aims to provide a critical understanding of management accounting techniques and practices and their relevance to contemporary business. The relevant concepts and theories, together with a range of emerging issues will be presented and critically evaluated.
  • Behavioural Finance (15 Credits) - Optional The purpose of this module is to introduce non-classical financial decision theory to acquire theoretical, methodological and practical knowledge of behavioural finance, to be able to apply this knowledge when analysing and assessing investment decisions, risk and uncertainty conditions in financial markets, identify factors that form irrational behavior, recognise the main anomalies of financial markets and assumptions for their formation, to understand causes and outcomes of irrationality in financial markets.
  • Derivatives and Structured Products (15 Credits) - Optional

    The aim of this module is to develop an understanding of derivative and structured products. The module will focus in particular on the rationale, mechanics and risk/rewards for investors in options, futures and forwards, exchange rate swaps, commodities and energy derivatives. A practical understanding of the pricing mechanics of derivative instruments will be developed. The module will also cover the applications of derivative instruments in hedging and investment. The structural and regulatory characteristics of each financial instrument and their respective markets will be emphasised.

  • Advanced Econometrics (15 Credits) - Optional This module introduces advanced econometric methods for the analysis of cross section, time series and panel datasets. Students are required to have knowledge of econometrics at the level of Applied Econometrics or similar before attending this module. A considerable advanced technical knowledge in econometrics and computer programming will be developed to address specific issues in financial econometrics, e.g., dynamic panel data analysis and ARCH/GARCH models. The aim is to deepen students’ analytical and programming skills necessary for empirical research in finance at advanced levels.
  • Data Mining (15 Credits) - Optional The quantity of data available to analysts is growing at an ever-increasing rate. This data has become a vital tool for decision making in a competitive world. However the size which makes the data so valuable also makes it difficult to anaylse using traditional statistical methods. This module introduces the student to a variety of methodologies now employed to explore, analyse, categorise and visualise data from large data sets and multiple related data sets. It also explores the issues with data sets that are too large even for established data mining methods (big data).

• Apply Now

• Enquire Now

• Request a Call

• Virtual Open Day