University of Edinburgh Business School

MSc in Finance, Technology and Policy

Semester 1

September–December

Compulsory courses

• Financial Markets and Investment
• Financial Valuation
• FinTech Infrastructures and Policy
• Principles of Data Analytics
• Python Programming

Semester 2

January–May

Compulsory courses

• Introductory Applied Machine Learning
• Modern Financial Market Microstructure

Option courses - Choose 2 or 3

• Blockchain, Governance and Policy
• Econometrics for Risk Analytics
• Economic Principles of Blockchain and Cryptocurrencies
• Ethics of Artificial Intelligence
• Financial Engineering
• Financial Machine Learning II (Practical)
• Investment Management
• Pattern Recognition in Financial Data
• Responsible Investing
• Technology Entrepreneurship and Commercialisation

Summer

May-August

Dissertation

Details of the Dissertation

As well as delivering a solid understanding of key theoretical finance and economic concepts, this Fintech MSc encourages potential future leaders to analyse and challenge the accepted financial setup.

Knowledge and understanding

By the end of the programme, students will be able to:

• Demonstrate an advanced knowledge of key theoretical finance and economic concepts underpinning financial markets
• Critically compare, contrast and evaluate the different machine learning techniques in terms of their applicability to solving problems in finance, this can be demonstrated by students using appropriate software to apply techniques to a given set of data
• Have an in-depth understanding of the relationships existing among the key global financial systems; for example, how bond yields dictate investment in equity and its derivatives
• Conduct valuation of financial instruments and projects within relevant regulatory contexts
• Trade financial instruments on exchanges/trading platforms by using state-of-the-art software packages and harnessing the power of relevant real-time financial data
• Demonstrate an appreciation of the role played by policies in shaping financial services delivery and financial markets
• Critically evaluate markets by being able to competently present arguments on the criticisms of the current set-up and offer the basis for the development of alternative technology-based markets and financial services products
• Demonstrate an appreciation of the social dimensions of technology use in financial markets

Graduate attributes

By the end of the programme, students will be able to:

• Demonstrate advanced numeracy and quantitative skills;
• Demonstrate authoritative and advanced knowledge of programming in a modern object-oriented programming language;
• Demonstrate the ability to develop and test research questions/hypotheses within finance either as part of a group or individually.
• Identify relevant data and demonstrate relevant retrieval and modelling skills.
• Demonstrate critical thinking skills and ingenuity required to identify and sustainably exploit opportunities arising from new and existing finance sector policy/regulatory initiatives.
• Demonstrate the ability to evaluate assumptions and statements based on data-driven evidence.
• Engage with new ideas and be able to detect false logic by leveraging available resources.
• Competently communicate and exchange ideas within different contexts and to audiences with varied compositions.
• Present reasonable and data-supported arguments in writing as well as orally
• Engage and work effectively within diverse groups.
• Effectively manage time and workload demands within a dynamic and challenging work environment.

Career Development

Graduates from the University of Edinburgh are highly sought after globally. Our dedicated Student Development Team within the Business School will be an integral part of your student experience from day one. We are here to help you become equipped to maximise your potential in the global market.

Graduate Employment

Potential roles available to graduates of this programme are varied across the finance sector, particularly in organisations exploiting big data. Examples of roles include:

• Data scientists
• Financial product developers/managers
• Financial/investment analysts
• Portfolio managers
• Quantitative regulatory analysts