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School of Economics and Finance

Professional Skills Development

We offer students opportunities to build practical professional skills that are relevant in the financial industry and are valued by employers.

Queen Mary MSc Investment Fund (QUMMIF)

QUMMIF is a student-managed investment fund with over £40,000 of assets. It provides postgraduate students with (i) work-relevant skills in investment, portfolio analysis, and trading as well as (ii) opportunities to network with fellow students, academics, and city professionals. Participants analyse companies, industries, and asset classes and develop practical investment and trading strategies. The work is done in teams which compete against each other to provide the best analysis. Academics and professionals from the financial industry act as mentors.

QUMMIF Team "Boondocks" consisting of Ramone Abbott-Jones (lead analyst), Chike Egbunike and Chidiebere Iwuanyanwu achieved remarkable success in the Worldwide Bloomberg Trading Challenge 2023. Competing against 2007 teams with 10,434 participants, the team ranked 53rd in the world and 11th in Europe."

Professional Development Modules

Professional Development Modules are optional, short, non-credit-bearing modules. They typically run for a few weeks at various points during the year and focus on practical skills such as programming or working with trading software.

Amplify Trading

Amplify Trading is a professional trading firm based in London. As well as a trading floor in The City, Amplify Trading have developed unique software to develop and assess new traders whilst making decisions within the uncertainty of live financial markets.

These systems are used to run the graduate programmes for institutions such as Bank of America and JP Morgan in New York, and HSBC and Deutsche Bank in London. Value lies in helping our students develop an understanding of live market dynamics as well as gain a firm grasp of the different roles and operations on both the buy side and sell side within the industry. Amplify Trading will run intense, two day trading programmes on campus to provide the same practical market exposure to students in the School of Economics and Finance.

Day one will expose candidates to live market trading as they experience executing investment decisions in response to application of fundamental and technical analysis.

Day two will cover a practical introduction to the workings a flow trading desk, exploring the roles within investment banking and fund management and the processes between them. Risk and portfolio management practises, client facilitation and trade execution are delivered through simulated activity where participants make markets through effective and clear communication.


Applied Portfolio Management

The aim of this course is to discuss modern investment theory, its central concepts, and practical applications. The purpose is to show the application of finance theory in making portfolio management decisions, with some emphasis on individual portfolio decision-making.

Property investments and leverage in an individual portfolio will be examined. Alternative asset management strategies will be studied in detail including statistical arbitrage, pairs trading and merger arbitrage. Hedging tools and a detailed overview of the delta hedging of options will be covered. Finally, a description and overview of structured products, how they are created and valued, their typical end markets, and how investors win or lose in these investments.



Students will learn the fundamentals of C++ with applications from quantitative finance and algorithmic trading. The course does not assume any previous knowledge of C++. During the tutorials students will perform interest rate curve interpolation and algorithmic hedging of fixed income portfolio; they will also design simple booking algorithms in C++ including derivative trades, positions, risk, and delta-hedging. Students will also study how to implement counterparty credit risk estimation for simplest derivatives. The course also introduces students to the various aspects of Standard Library in C++ where the algorithms and data structures are implemented. Throughout the course, the sample questions from quant interviews and the solutions to them are presented.


Finance Trading Programme

FTP provides a working theoretical knowledge and a practical understanding of financial markets, trading strategies, risk and money management and trader analytics at the highest level.

The program offers a mix of classroom-based teaching, case study and practical trading exercises where students will trade on real-time simulated global markets through the use of industry-strength proprietary trading software (such as Bloomberg, Thomson Reuters Eikon, X-Trader and others) in the School of Economics and Finance’s trading room.



MATLAB, a high-level language and interactive environment, is used for numerical computation, visualisation, and programming. The module will cover fundamental concepts such as data structures, function creation, and algorithm development. Emphasis will be placed on practical applications, allowing students to implement complex mathematical calculations and develop graphical user interfaces for data analysis.


Python for Finance

The focus of the course is on working with Python to analyse financial markets. The course begins with an introduction to Python and the general syntax of the language. We then move on to (i) working with the data science libraries in Python such as NumPy (for linear algebra) and Pandas (for time series) and (ii) doing visualisations with libraries like Matplotlib and Plotly.

We discuss how to access market data from many different sources in Python, and how to backtest systematic trading strategies in Python with a focus on FX markets. We also talk about how to conduct event studies in Python. We show how we can use Python with Excel and also to create web dashboards. Python code examples are provided in Jupyter Notebooks.

VBA for Finance

The course will teach students VBA in Excel with applications to finance. The course does not assume any previous knowledge of coding or Excel. The course structure is:

    • Excel Introduction
    • VBA Introduction
    • Analysis of financial data
    • Financial market case studies using VBA and Excel


Students provide free financial advice to local tech start-ups and entrepreneurs. The work is supervised by experienced professionals from leading organisations. Students provide advice on matters such as developing a business plan, data analysis, sources of funding, business structures, and marketing.


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