Student experience

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From: China

Currently working: on PhD applications for further study in stochastic analysis

The reason I chose the CMF programme is that I am skilled in math and its application in finance attracts me a lot. The decision turned out to be the totally correct one. Over the course of the year, my quantitative finance skills like stochastic analysis, programming skills like Python, and research skills for mathematical finance are all improved by the professional trainings.

From my perspective, the CMF programme is flexible enough that caters to varies needs of students. Apart from compulsory courses, there are three streams with different courses to choose, which allows us to concentrate on the skill that we prefer to improve. Additionally, there’s an option of ‘class only‘, which allows students to join the class without costing any credit. Moreover, plenty of topics for dissertation are offered, and teachers from different universities all around UK are invited to be our supervisors.

Every teacher here is patient and responsible. Since there is a lot of material I haven't studied before, I will be honest and say that I feel a little bit overwhelmed throughout the first semester. Fortunately, the teachers will always respond to our questions via email or in person. Additionally, there is a workshop every week for each session where we can ask any question we may have. With their help, even though the second semester was more challenging, I still managed to complete it.

The city of Edinburgh is undoubtedly a great place to live and study. Thanks to the quiet environment, the lovely city view and wonderful hues in the sky, I had a comfortable and memorable stay there. Due to the unforgettable memories, I’m thinking about pursuing my further studies in Edinburgh.

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From: China 

Majoring in both Physics and Economics in my undergraduate study, I developed a great interest in quantitative finance, especially applying computational skills and mathematical models to solving real-world financial problems. Therefore, I applied for the CMF programme which proved to be a fantastic choice. 

The CMF programme provides a variety of compulsory and optional courses covering different aspects of mathema

tical and computational finance, from theory to applications. Three streams of courses are available for students to choose from according to their own preferences. The financial stream is a perfect option for those interested in modern financial theory. The computational stream focuses more on cultivating students’ ability of numerical analysis and practical skills. And I chose the Machine Learning stream. The courses, like Machine Learning in Python and Reinforcement learning, honed my programming skills and helped me gain deeper insights into applying machine learning techniques to finance. I believe every students can find courses align with their interest in the programme. 

The programme is well-structured as well. All foundation courses are in the first semester and these courses are regarded as the pre-requisites of more challenging courses in the second semester. And the courses in the second semester will practice what you have learned. This progressive structure ensures that all students, even those who are new to the field of mathematical and computational finance like me, can gain deep understanding of this area. My favorite course is Stochastic Control and Dynamic Asset Allocation in the second semester which requires both good knowledge in stochastic analysis and Python skills to implement optimal control algorithm solving financial problems, like Merton problems. After taking this course, I decided to choose the topic of solving optimal control problems by reinforcement learning techniques in the dissertation, and the work is related to my current job. 

Although this academic year was a tough year for students as all courses were held online due to Covid-19, the lectures and workshops were still well prepared, and students can always get help from the lecturers and classmates through Q&A on Piazza. I would say that studying in the programme of Computational Mathematical Finance was really a fantastic and meaningful experience for me. 

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From: China

Currently working: as a Quantitative Research Analyst for a leading security company

The Computational Mathematical Finance programme at the University of Edinburgh is an excellent option for students to further tailor their essential mathematical skills for quantitative financial study. For me, this programme perfectly connected my previous mathematics knowledge with financial related problems, and this was the main reason I chose this programme. 

The program consists of two semesters with one 3-month dissertation project. Those compulsory courses are set to ensure you are prepared with essential bits of fundamental knowledge for your courses in Semester 2. Alongside your compulsory courses, you can take some optional courses. An attractive part of the free selection of optional courses is that students can enrol in other Schools’ courses if they have permission. I picked a course from the School of Informatics to enhance my Python skills, which is really helpful for my career. I found my studies became more challenging in Semester 2 as we were introduced to more real-world modelling problems and more advanced theorems. The most challenging topic for me was the stochastic control, which contains not only stochastic calculus but complicated mathematical models. Fortunately, the teaching staff are knowledgeable, welcoming and always ready to help. You will feel you have really improved after finishing Semester 2.

The School works closely with industrial partners, offering students the chance to have valuable experience working in the industry. I worked with Moody’s Analytics for my dissertation on a topic which was a cutting-edge problem that the company was working on.  The CMF programme can improve students in many aspects. Although it is challenging, it is extremely rewarding. I am now working in the quantitative research team in a leading securities company and I believe this programme must be a huge factor in this.

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From: China

Currently working: on PhD applications for further study in stochastic analysis

When I was in the undergraduate study, I realized the importance of an MSc which will help me find a job or pursue a PhD. Then I decided to choose the University of Edinburgh which was attractive to me. According to my major of the undergraduate study: Financial Mathematics, I found that the Computational Mathematical Finance MSc programme would be the best choice for me, which was much more practical and theoretical than my undergraduate study. I would be equipped with the “strong” courses and practices, and I may be more competitive in my future career.

After I arrived in Edinburgh, I knew I made a wise choice. I love Edinburgh, and I also love the life in Edinburgh. I not only could have lectures and discuss with tutors in JCMB, acquire knowledge and do programming at the main library, but I also enjoyed spending time with my friends at the Calton Hill, The Meadows and Portobello. Although my studies were challenging, in Edinburgh, my life was always fulfilling and wonderful,

I tried my best to get over all difficulties in my studies and I realized many doors are opened by the difficult courses and the challenging programming practices by studying this MSc, which means I have more choices in my life because I have the strong and competitive mathematical background now. I think I will work one or two years in the financial area, and then I may pursue a mathematical PhD in the future. In my opinion, the University of Edinburgh is still my dream school, and I will work hard to make my dream come true.

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From: Czech Republic

After completing my undergraduate degree at the University of Edinburgh, I decided to stay for an additional year to do the Financial Modelling and Optimisation programme. This programme developed my mathematical skills in a completely new way, as I had never studied anything related to finance before. I was nervous about doing a financial master’s with no prior knowledge of finance, but we were given enough support that this was not a problem for me. I was also given an opportunity to learn programming, which has definitely been helpful when applying for jobs. In my opinion the best part of the programme was the option to do our dissertation in cooperation with an industrial partner. My dissertation was done in cooperation with Moody’s Analytics, and it was focused around modelling the interaction between the climate and economy, which was a very interesting topic for me. 

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From: The Netherlands

Currently working: on PhD applications for further study in mathematical finance

During my undergraduate studies in econometrics and operations research, I developed a strong interest in financial theory. Especially topics such as derivative pricing, risk hedging and portfolio optimization, where we apply mathematical theory to present-day problems in the financial markets, appeal to me. Moreover, I am very curious to other cultures and after studying abroad in Sweden for a while, I realized I wanted to go to a foreign country again for my graduate studies. Considering that Edinburgh attracts many international students and the fact that the University of Edinburgh is one of the most prestigious universities in the UK contributed to my ambition to study at this university.

Choosing to study in Edinburgh truly proved to be the best choice I ever made. The FMO programme turned out exactly like I was hoping: a very intensive, in-depth study of financial theory in mathematics. The year has been extremely challenging and rewarding. There are plenty options to tailor the programme as you wish. For me, that meant a more theoretical approach to financial mathematics by choosing my electives and dissertation project accordingly. Other students may favor a more practical/applied programme, for whom the option to engage in an industry-based dissertation project is provided. The lecturers and other university staff are very approachable and try their best to offer support with any issues you may encounter during the year. I was particularly impressed by our personal tutors’ involvement in our studies.

Besides its excellent universities, the city of Edinburgh has a lot more to offer. I absolutely fell in love with the city and its people and cannot wait to hopefully move back to Edinburgh in the future.

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From: Ireland

Currently working: as a Quantitative Analyst for Moody's Analytics

I decided to do an MSc in Financial Modelling and Optimization here in Edinburgh to focus and hone my mathematical skills in the financial sector. I found that my undergraduate degree in Mathematics gave me very valuable analytical and problem-solving skills but did not contain many courses aimed specifically at financial maths. As a result, I found myself looking to develop my skills further and couldn't have chosen a better place than The University of Edinburgh to do that.

The MSc offers an extensive range of courses aimed at developing quantitative skills such as Stochastic Analysis in Finance, Stochastic Control and Optimization Methods in Finance, as well as courses aimed at developing computational skills such as Machine Learning in Python and Numerical Probability and Monte Carlo Methods. The lecturers and staff are extremely qualified and are always more than happy to help with any questions you may have. This was one of the things I liked and benefited from most in the year I spent studying here.

I loved Edinburgh as a city and have made some friends here that I will have for life. There's a great mixture of social and cultural activity, and I never once found myself bored on the weekends with nothing to do. There are also plenty of interesting employment opportunities to be found in Edinburgh after completing the MSc. I ended up finding a job in Edinburgh as a Quantitative Analyst that began a few weeks after I finished the dissertation period of the MSc. I've found that the MSc has prepared me extremely well for a career in quantitative finance and most of the content that I'm seeing in this role was covered in the MSc.