专业：Finance, Technology and Policy
链接：
https://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&edition=2018&id=966
课程设置：
You will be required enroll on eight compulsory courses worth 90 credits and option courses worth 30 credits. You will also write a dissertation worth 60 credits.
Learning will be primarily through formal lectures, seminars, workshops, flipped classes, practical computer labs sessions, student presentations, guest speakers, master classes, research assignments, and the research dissertation. Delivery of the taught element of the programme is primarily via a combination of lectures, seminars and workshops.
Assessment methods include examinations, reports, essays and team presentations.
Learning outcomes
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. Demonstrate by 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.
入学要求：
A UK first-class or 2:1 honours degree in one of the subjects below, or an equivalent overseas qualification.
An undergraduate honours degree in finance, economics, engineering or informatics is normally required.
You will need to have taken and passed at least one course with significant statistical analysis and/or programming as part of your undergraduate degree or be able to demonstrate that you have relevant work experience in the use of statistical and/or programming software packages.
Candidates with a first class or 2:1 honours degree in other disciplines will be considered on an individual basis if some level of finance/economics/informatics content formed part of the degree and you can demonstrate a high level of quantitative ability through your degree results.
Candidates with a first class or 2:1 honours degree in an unrelated subject area but have relevant work experience will be considered on an individual basis.
Candidates with a first class or 2:1 honours degree in an unrelated subject area but who have relevant professional qualifications will be given due consideration on an individual basis.
If you are a mature candidate with significant finance and tech industry experience or with relevant professional qualifications, you will be given due consideration on an individual basis.
IELTS: total 7.0 (at least 6.0 in each module)