University of Oxford - MSc Mathematical and Computational Finance

Lectures - 8/10:
The lectures were generally of good quality, except for some guest lecturers which did not live up to the same standard as the university ones. The content was generally challenging (and could be very challenging without a solid background), but delivered well. My main complaint is that they often felt crammed in to 16 hours due to nature of the Oxford term structure where other universities would offer 20-30 hours to cover the same content.

Seminars - 5/10:
The quality of the seminars was largely dependant on the DPhil student delivering the class (as with many universities). There were some courses which had very useful and informative seminars, but many which were poor and disengaging. This was often made worse by them being held in large lecture theatres (likely due to increased numbers of students on the course), meaning there was often little student engagement.

Careers - 7/10:
I'm quite torn with this one. I (naively) started the year thinking that having this course on my CV would walk me relatively easy into an entry level quant job - this is not the case. In the end the whole application cycle was completely demoralising with little support but a lot of pressure from the course director and other students to keep on
applying. However, I ultimately did walk away with two internships (one as a dissertation organised through the university and one off my own back), so in a sense the process worked. Hence I would say the university does everything you would expect it to to help you, with a decent careers service, and does organise dissertations in industry for some students, but does not go to the lengths some other courses do.

Exams - 8/10 (written papers), 7/10 (C++), 2/10 (Stats/DL):
The written exams are as you would expect (although it can be difficult to prepare with no revision lectures or solutions to past papers). By far the worst exams are the 48hr Deep Learning and Stats exams. While being open book eases revision, they encourage people to work through the night and are horrendous.

Student Experience - 3/10:
The intense and short nature of the course makes the student experience hard and isolating, with occasional parts that make you remember you're at Oxford (like matriculation and formals). As with any degree, it's what you make of it, but the workload on top of the internship applications makes it hard to find time to do other stuff compared to standard 12 months MSc with a bit more time.

Misc:
- Despite the above, the name of this course and the Oxford name goes a long way.
- The introduction week is horribly intense and can feel completely overwhelming, and was actually much worse than the main course for me. Try to prep some stuff in advance (particularly probability theory) if you can.
- I would not recommend this course for people wanting to do PhDs - they barely talk about them and this year of studying was so intense it put me off doing one (and it's way more expensive for most people than the 4th year of an integrated masters).

Pros:
- the whole Oxford experience, i.e. collegiate system, formal dinners, networks, meeting people from various background
- course introduces you to the main concepts in mathematical finance and related mathematical backgrounds (although given that the course is only 9 months long, it is often not that rigorous)
- the Oxford name for applications

Teaching: In general, the teaching quality is average to good. However, it varies significantly between different lectures (i.e. there are some with rather poor quality for Oxford standards). In contrast to undergrad teaching, there are no tutorials with 1-3 students but classes with -20 students taught by (mostly) DPhil students (hence of varying quality). Many professors tend to use slides (which I personally do not like for lectures focusing on mostly mathematical concepts, proofs, etc.)

Assessment: Exams/Take-Home Exams/Online Exams happen at the beginning and end of the Christmas and Easter break (i.e. December, January, March, April), so most of the time in the break has to be used for studying. Deep Learning and Statistics are 48h hour take-home exams/projects which can be quite exhausting. Moreover, in the written exams multiple lectures are assessed in one sitting (e.g. Stochastic Calculus and Financial Derivatives, or Fixed Income, Stochastic Control and Risk Management).

Dissertation: In the last term (i.e. Trinity) there are no lectures/classes, only the dissertation. Nevertheless, due to the short timeframe (-10 weeks) it can still be stressful. The Maths Institute provides a list with possible dissertation topics. Alternatively, the dissertation can be done as part of an internship. The quality of supervision is also very dependent on your supervisor (and/or industry supervisor if you are doing an internship)

Basic Stats
# of Students: 29
# of Applications: ~500 (bear in mind the admission test narrows this down considerably vs. other schools)
Length: 10 months
Cost: ~25k GBP (tuition and college fees) + 1-2k living costs per month?
This should be on the website: https://www.maths.ox.ac.uk/courses/mathematical-finance/msc-mcf

Employment Statistics
Post graduation employment statistics aren't given so I'll give this year's breakdown from what I know.

Full Time: 5 - 7 (2 had return offers from before the course)
Internships: 6 - 9
Further study: 1 - 3
(Statistics taken just before the end of the course - no doubt some will find jobs after the course etc..)

From my sources, previous cohorts also had similar employment statistics at this stage in the course.

All jobs are based in London, except for 1 in Europe, 1 in Hong Kong and 1 in the US.
Employers include the top tier IBanks, a quant hedge fund and a trading firm.

You will get (some) interviews from the reputation of Oxford mathematics but this alone will not secure you a job.

What I liked
General Oxford experience - old architecture, punting, societies, Oxford Union etc...
Top notch facilities - especially the new Mathematical Institute building. It's arguably the coolest math building in the world :D.
Excellent teaching - Apart from one or two lecturers, the quality of teaching is exceptional. You are taught by some fairly big names in financial mathematics.
Solid coursework - The coursework is very rigorous and a lot more theoretical than other programs. The overall focus of the course has been on derivatives pricing although you have an option next year to focus on data-driven topics e.g. algo trading and market microstructure.

What I didn't like
Course structure - This is by far the biggest complaint among the current students and to Oxford's credit the course will be restructured next year (2014/2015) in light of this. We learned programming far too late to be useful in interviews and were expected to find jobs at the very beginning of the course when the graduate recruitment season began.
C++ Programming Courses - You learn the basics and then learn how to use and extend the lecturer's own library. This is inadequate preparation for quant interviews and actual quant work. You will need to study some Comp. Sci (e.g. sorting algorithms) yourself.
Course is too intensive/long. The course tries to pack in too much material for the 10 months and as a result you will be pressed hard. By the start of the final semester only less than 40% of the course marks have been assessed. Make no mistake - this course is one of the most difficult in Oxford.
No careers service - you have a careers office (outside of the department) but nothing else. No one is actively searching for roles for you unlike at some top US programs. You might also get some networking sessions/presentations from banks/HF's but that's about it.
What I'm neutral about
Dissertation and Miniprojects - These were very time consuming - you need to do all of these during Trinity term. That's around 60-80 pages of stuff you are required to write in 8 weeks or so. On the other hand, these projects were a good way to reinforce material learned in the first two semesters.
Overall opinion
Overall, the course was stimulating and engaging - definitely worth the money. Although the course wasn't as great as I expected it to be, it was still excellent.

Advice for potential applicants
If you want to pursue a DPhil/PhD, this program is for the most part theoretical enough to help you in admissions interviews especially in stochastic processes/PDE's. The issue is with timing - ideally you should apply towards the end of the course when you have marks and know the faculty better but unfortunately the isn't usually the case.

If you want to apply hoping to find a quant job after graduation, my advice is to be prepared.
Students with no experience in finance beforehand only managed to secure internships at best. Those students who managed to obtain full time work had internships behind them and the Oxford brand only helped to land interviews. The job hunt begins as soon as you arrive - banks' graduate recruitment opens near the start of the course. You will not have had sufficient time to study programming/brainteasers/stochastic calculus etc. to succeed in any early interviews. Statistics/Time-series analysis are also useful skills to have going into the course.

Also Oxford's location should not factor into your decisions - the bus to London takes only 1-2 hrs.

US vs. UK
The top US quant finance programs (Columbia, CMU, Princeton etc.) have better careers services - they have active alumni recruitment programs or whatever they call it.
US programs are longer (1.5-2 years) and UK programs are shorter (1 yr). More time to get internships and to land that full time job.
In the US you get jobs via networking and over here you have to apply online mostly.
The US market seems a lot more competitive than in the UK.

It feels like that there are more investment banking quant jobs in London but fewer prop shop or hedge fund jobs.

What other courses should I consider (in the UK)?
Imperial has better careers services and employment outcomes - I'd do their industrial training over a dissertation anyday! LOL
Cambridge Part III is cheaper and just as employable/reputable as Oxford, imo. However, some say it's even more 'hardcore' than even the Oxford MSc MCF.
I don't know about LSE but my fellow students say its much worse than Oxford.

Frankly, you will have difficulty finding quant jobs if you are in lower ranked universities. Banks' tend to hire from Oxford, Cambridge, Imperial, LSE in no particular order.