LSE MSc Financial Maths or UCL MSc Computational Finance?

Hi! I recently received unconditional offers from these two programmes and I'm confused about which one to choose.

Basically, LSE has a probably better reputation however I'm not sure if the prestige in IB moves to quant as well. Moreover, the LSE course seems to teach theoretical modules in option pricing/stochastic/derivatives and lack in coding. That may narrow the career path to sell-side quant doing pricing and derivatives only.

On the other hand, UCL CF offers Machine learning and Data science courses which from my perspective would be practical and helps me explore quant research/trading jobs in bank and HF. Plus, it secures an industry project that guarantees a work experience. The point is that I did my undergraduate at UCL so the master programme doesn't level me up in terms of brand.

Any advice???
 

Daniel Duffy

C++ author, trainer
My 2 cents
A school that doesn't do programming (or coding as it is quaintly called) is not exactly future-proof.
ML and DS are trendy, but how widespread is it really? I have no idea...

I would learn C++ and Python.
 
My 2 cents
A school that doesn't do programming (or coding as it is quaintly called) is not exactly future-proof.
ML and DS are trendy, but how widespread is it really? I have no idea...

I would learn C++ and Python.
Thx, I'll take that into account!!!
 
LSE grads might get IB jobs easily but quantitative finance is a specialised and a rapidly evolving field. Please go through the thread below before you decide.

Thread 'PhD in Hong Kong or MFE in the states?'
PhD in Hong Kong or MFE in the states?
Thank you for sharing this thread it's helpful. One more question, how helpful is the LSE finmath master in terms of landing a job in LDN or HK, and how does it compare to the UCL one, with less reputation but more practical in coding?
 
I’m not sure about the job scenario tbh but I think someone on this forum with an amazing profile asked about joining Imperial. Maybe check the curriculum for that program.

For UK, you better learn to code, if you want to work in good roles. As far as I remember LSE MSc Finance students did code in Python/R in 1 or 2 electives (optional), not sure about LSE FinMath.
 
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I’m not sure about the job scenario tbh but I think someone on this forum with an amazing profile asked about joining Imperial. Maybe check the curriculum for that program.

For UK, you better learn to code, if you want to work in good roles. As far as I remember LSE MSc Finance students did code in Python/R in 1 or 2 electives (optional), not sure about LSE FinMath.
Hello everyone hope your all good could I also have your opinion on my situation?

 
Hi! I recently received unconditional offers from these two programmes and I'm confused about which one to choose.

Basically, LSE has a probably better reputation however I'm not sure if the prestige in IB moves to quant as well. Moreover, the LSE course seems to teach theoretical modules in option pricing/stochastic/derivatives and lack in coding. That may narrow the career path to sell-side quant doing pricing and derivatives only.

On the other hand, UCL CF offers Machine learning and Data science courses which from my perspective would be practical and helps me explore quant research/trading jobs in bank and HF. Plus, it secures an industry project that guarantees a work experience. The point is that I did my undergraduate at UCL so the master programme doesn't level me up in terms of brand.

Any advice???
I have the same two offers of LSE MSc Financial Maths and UCL MSc Computational Finance for this year. I chose UCL because its course is computational based while LSE is theoretical. For me, the outlook is to pursue a quant career right after masters so UCL is better fit as it gives you the statistical and computational skills to work on algorithms and models. While I would say if someone prefers to pursue PhD after masters should opt for LSE as most students in that course opt for that because the course's theoretical dominance is perfect for research and further study purposes.
 
I have the same two offers of LSE MSc Financial Maths and UCL MSc Computational Finance for this year. I chose UCL because its course is computational based while LSE is theoretical. For me, the outlook is to pursue a quant career right after masters so UCL is better fit as it gives you the statistical and computational skills to work on algorithms and models. While I would say if someone prefers to pursue PhD after masters should opt for LSE as most students in that course opt for that because the course's theoretical dominance is perfect for research and further study purposes.
Have you started the course, how are you finding it so far? Also can someone from non-math degree enter this programme with finance and data science modules?
 
Have you started the course, how are you finding it so far? Also can someone from non-math degree enter this programme with finance and data science modules?
Yes, I am currently pursuing the course and it has been a thrilling learning curve.

I think every student struggles in some aspect of the course. Because everyone come from different degree backgrounds and UCL MSc CF will require or build your knowledge in mathematics/physics, programming and finance/econ. I have a math undergrad but still mathematics is crazy work (as every university and professor teaches topics differently) from what i have seen in 1st Semester - I have physics, econ friends who are doing as well as I am. The first semester feels like completely theoretical because we didn't have significant focus on coding. I believe any student from any degree background can pursue this MSc because every single person (sparing some geniuses) in my program find it challenging and truly for me that is the thrill of studying such an expensive programme of learning a whole new skillset / knowledge.

Only advice: You can really do this if you have focus from the start and keep on studying what they are teaching in lectures - or what is in the portion because there are some professors who are really bad at teaching so you have to cover their modules by yourself. There is no help from uni to build your basics in mathematics or programming - you are on your own mate, only thing they will give you are a refresher notes pdf (primer) on mathematics and coding basics, and based on that a recorded module page like you have a recorded long course on Udemy. While this may seem a lot of negatives, but so is the difficulty of the work done in quant roles in the finance industry - but you always have other students in the programme who are ready to help you in and collaborate. As per my knowledge, I am the only South Asian in the course, yet I have made amazing friends of varying cultures and backgrounds in the programme.
 
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