Even before the 2008 Financial Crisis, investment finance was becoming increasingly globalised, complex and reliant on information technology to create and manage financial asset portfolios, private equity, and hedge funds. This MSc Investment Management has been created to reflect the latest developments in finance theory and in the investment finance industry.
The programme is designed to enable you to use technology to create and manage your own investment portfolios, or to effectively manage clients’ portfolios or wealth funds if you work in the financial services industry.
You will be introduced to technological innovation, such as machine learning, big data analysis and algorithm trading, and will have unlimited access to the Financial Markets Lab, where you can set up or simulate your trades in FX, equity and derivatives markets.
The course uniquely combines theory and applications of finance, machine learning, and big data analysis. If your interest is in managing wealth funds or in corporate finance, this course will provide solid knowledge in accounting and financial management.
This course covers all aspects of the finance and wealth management industry, such as corporate finance, entrepreneurial finance, financial and managerial accounting, portfolio theory, and investment analysis and management. It also incorporates quantitative and computational methods applied to portfolio analysis and management, the theory and use of securities and derivatives, and to the accounting and financial management of wealth funds.
This programme will give you theoretical and applied finance knowledge as well as computational, statistical and numerical foundations that will enable you to pursue a career in financial technology (“Fintech”).
This module provides a sound grounding in the theory and practice of investment analysis and management. You will develop your knowledge of key concepts and tools, and you will be required to apply these to analyse real life financial assets.
This module will equip you with the theoretical and (mostly) practical tools to value financial assets, gauge capital allocation decisions and critically analyse corporate finance theories while applying them to real live companies.
This module aims to deepen your knowledge of fixed income products. You will develop your practical understanding of the pricing mechanics 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. You will also focus on the Bloomberg Financial Database and gain an understanding on the concepts, valuation principles and application of financial derivative products.
This module deals with basic statistical methods and explores the application of these methods to analytical models in finance. You will be provided with the analytical and programming skills necessary to pursue empirical studies in finance. You will be encouraged to use previous knowledge in statistics and computer programming.
This module will give you an awareness and understanding of the mechanics, challenges and issues related to the different ways of financing an enterprise.
This module examines the evolution of corporate governance and accountability mechanisms from theoretical and practical viewpoints. You will elevate your knowledge by critically discussing topical issues in corporate governance and social reporting, such as high profile cases of corporate failure, and understanding how such mechanisms can be applied to enhance corporate accountability. The module highlights the significance of corporate transparency and the links with corporate accountability.
This module provides you with a critical understanding of the financial accounting techniques and practices and their relevance to contemporary business. You will also evaluate the impact of international regulatory frameworks on these practices.
This module provides you with a critical understanding of management accounting techniques and practices and their relevance to contemporary business. You will critically evaluate the relevant concepts and theories, together with a range of emerging issues.
This module develops your understanding of derivative and structured products. You 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. You will also develop your practical understanding of the pricing mechanics and the applications of derivative instruments in hedging and investment. You will explore the structural and regulatory characteristics of each financial instrument and their respective markets. You will also focus on the Bloomberg Financial Database and gain an understanding on the concepts, valuation principles and application of financial derivatives.
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 analyse using traditional statistical methods. This module introduces you to a variety of methodologies now employed to explore, analyse, categorise and visualise data from large data sets and multiple related data sets. You will also explore the issues with data sets that are too large even for established data mining methods (“big data”).
This module introduces advanced econometric methods for the analysis of cross section, time series and panel datasets. You will develop an advanced technical knowledge in econometrics and computer programming in order to address specific issues in financial econometrics, such as dynamic panel data analysis and ARCH/GARCH models. You will deepen your analytical and programming skills necessary for empirical research in finance at advanced levels (MPhil and DPhil).
You must have completed the Applied Econometrics module if you wish to study this module.
This module will introduce non-classical financial decision theory to acquire theoretical, methodological and practical knowledge of behavioural finance. You will be required to apply this knowledge when analysing and assessing investment decisions, risk and uncertainty conditions in financial markets. You will identify factors that form irrational behaviour and recognise the main anomalies of financial markets and assumptions for their formation. You will also understand causes and outcomes of irrationality in financial markets.
This module will focus on information and communication technology in order to carry out financial market analysis in detail. You will develop key skills to implement computational approaches towards financial problems. You will also have the knowledge to handle, manage and analyse financial data using Visual Basic and Excel.
This module will introduce the concept of risk measurement and analysis of financial data. You will gain the knowledge and basic skills required for risk measurement, technical analysis of financial data, investment decision-making, portfolio selection and optimisation.
You are expected to have basic knowledge of probability theory and statistics at undergraduate level before studying this module.
This module provides you with the opportunity to select your own specialised research topic in the area of financial management. You 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 and methods whilst conducting your research. You will be required to independently plan, organise, and coherently produce a limited but a well-researched work.
You can find more information about this course in the programme specification. Optional modules are not offered on every course. If we have insufficient numbers of students interested in an optional module, or there are staffing changes which affect the teaching, it may not be offered. If an optional module will not run, we will advise you after the module selection period when numbers are confirmed, or at the earliest time that the programme team make the decision not to run the module, and help you choose an alternative module.
You will be taught through a variety of lectures, seminars and tutorial and will be encouraged to develop your self-directed/ independent learning. You will attend workshops and lab sessions where you will be taught to use specialist statistical and data mining software.
You will also benefit from guided online learning activities as well as exclusive use of the Financial Markets lab with 12 Bloomberg and Datastream platforms.
You will mainly be assessed through individual and group coursework. Exams are limited to the 30 credit module that provides the foundation of the degree, and to one 15 credit module in Applied Econometrics.
Career prospects for this course can include:
Dr Gottschalk joined Middlesex University Business School after several years as a researcher and forecaster at the National Institute of Economic and Social Research (NIESR). She has worked on a wide range of topics in applied economics, such as exchange rate volatility, macroeconomic and credit risk modelling. Recently, her work has focused on the impacts of the Basel Capital Accord in emerging markets, on the development of macroeconomic measures of credit risk, and on the macroeconomic determinants of FDI, in particular, on the impact of exchange rate uncertainty and monetary union on FDI to the UK and on the location decisions of US and Japanese firms in East Asia.
Dr Deshmukh joined Middlesex University Business School in 2012. Before joining academia, he worked for several years in industry as a successful fund manager. Based on his industry experience, Dr Deshmukh has developed two cutting edge modules in Equity Analysis and Fund Management. He is also an internationally reputed researcher and is currently supervising several PhD students and has served as an internal and external examiner for PhD vivas. Students have consistently rated him as an excellent teacher.
Dr Lodh joined the Middlesex University Business School in 2012 after several years of industry and teaching experience in India at undergraduate and postgraduate levels. He has been published in highly ranked international journals including the Corporate Governance: An International Review, International Review of Financial Analysis as well as in Industrial and Corporate Change. His research works have been presented in a number of highly rated American and European conferences including the prestigious American Accounting Association Annual Conference and European Accounting Association Annual Conference. He also serves as an ad-hoc referee of several top-ranked academic journals.
Dr Parsa is the PhD coordinator for the Accounting and Finance Department. His main research interest is in corporate accountability and social reporting with a focus on ‘labour’ and ‘human rights’ related issues in both developing and developed countries.