Best UK Master's course for becoming a quant?

[academicweb]

Hi all,

I'll be graduating from a decent UK uni this year with a BSc in Mathematics. I've been given 3 conditional offers for:

• Cambridge MASt Applied Mathematics,
• Imperial College London MSc Mathematics and Finance,
• LSE MSc Financial Mathematics.

My ambition is to become a quant, and I realise that the two financial mathematics degrees are obviously designed for people wanting to go into quant etc., but they're both about 3 times the price of the Cambridge course, and realistically I'd enjoy the Cambridge experience a lot more (course and city).

Any advice as to which of these I should go for would be much appreciated.

Thanks!

 

[lolalin]

From what I understand anyways, the top MFE programs in the UK are Imperial Math and Fin and Oxford MSc MCF. Also from what I've read on QN, tripos should also be a target. From what you state, the Cambridge course should be a no brainer.

 

[David Liam]

Cambridge is stronger than the rest in terms of brandname and also it gives you very strong understanding of math and you can learn coddin yourself, I would go for cambridge

 

[cheron_jrm]

Part iii student here.

I think the course is of very high quality, as you would expect. However, this does not prepare you to be a quant, be aware of that. I mean, you won’t learn to code, learn any finance nor do any project based course to apply your knowledge. The aim of part iii is to prepare for maths research. For me, this was not a problem as I came from a computational maths background so I’ve done a lot of programming/applied maths.

That being said, it is a target for buy side jobs, and I’m sure no bank would reject part iii resume’s. So finding a job will not be a problem after part iii.

I had offers from Imperial & Oxford Maths Fin in the UK, and chose part III because I thought doing stats would compliment my background more (and because doing maths at Cambridge is something to do if you can imo), and because I wanted to work in a hedge fund, which value more stats/ML than traditional maths finance. However, if you think you need to practice programming in courses, want to have projects, and finance-relates course, Imperial is one of the very very best programs in Europe, with a way curriculum than Oxford in my opinion.

 

[Daniel Duffy]

The aim of part iii is to prepare for maths research.
This is not exactly what is needed in finance.

If you do pure maths, you miss out on {numerical, applied, computational} maths. Just sayin'

And you have to be good at programming.

 

[cheron_jrm]

@Daniel Duffy Indeed, it is target because students are well selected and are prepared to learn new things, not because of their skills !

 

[Daniel Duffy]

@Daniel Duffy Indeed, it is target because students are well selected and are prepared to learn new things, not because of their skills !

It depends. Maths is not a magic elixir.
I did all that pure maths stuff, but much of it is not so useful for finance.
Being good at X means you are good at X.
Analogy; a judoka is a useless karateka and vice versa.

 

[Daniel Duffy]

I had a look at the syllabus, good content

Part III Guide to Courses | Part III (MMath/MASt)

www.maths.cam.ac.uk

It leans more to theory than applied. Just saying.

Do you learn Navier-Stokes PDE?

 

[cheron_jrm]

It depends. Maths is not a magic elixir.
I did all that pure maths stuff, but much of it is not so useful for finance.
Being good at X means you are good at X.
Analogy; a judoka is a useless karateka and vice versa.

It is true, though I would not be surprised if a good judoka could learn karate and become better than average pretty easily. I think that's the idea behind hiring Cambridge math students rather than some other financial maths students.

I had a look at the syllabus, good content

Part III Guide to Courses | Part III (MMath/MASt)

www.maths.cam.ac.uk

It leans more to theory than applied. Just saying.

Do you learn Navier-Stokes PDE?

I focus on stochastic processes and statistics. I did not study PDEs/Analysis.
It is true the program focuses on the math rather than its applications. That explains why the Statistics/Probability courses are in the Pure department. An example I can provide is the way LASSO is treated. We do study and prove the rates of convergence of the forecasting errors, and study random designs to evaluate how likely are the conditions necessary to have the fast rate, but we don't fit the model on any data.
To be fair, there is a course which implies a little bit of R coding. But the aim is to illustrate and understand the models, not to develop modeling skills.

 

[academicweb]

Part iii student here.

I think the course is of very high quality, as you would expect. However, this does not prepare you to be a quant, be aware of that. I mean, you won’t learn to code, learn any finance nor do any project based course to apply your knowledge. The aim of part iii is to prepare for maths research. For me, this was not a problem as I came from a computational maths background so I’ve done a lot of programming/applied maths.

That being said, it is a target for buy side jobs, and I’m sure no bank would reject part iii resume’s. So finding a job will not be a problem after part iii.

I had offers from Imperial & Oxford Maths Fin in the UK, and chose part III because I thought doing stats would compliment my background more (and because doing maths at Cambridge is something to do if you can imo), and because I wanted to work in a hedge fund, which value more stats/ML than traditional maths finance. However, if you think you need to practice programming in courses, want to have projects, and finance-relates course, Imperial is one of the very very best programs in Europe, with a way curriculum than Oxford in my opinion.

Thanks a lot for the response. Could you possibly inform of your background regarding any industry experience you have, and if you've successfully managed to land a job offer for after you graduate? Part III is of course supposed to be pretty difficult - do you find you have enough time to spend on career related things? I, unfortunately, haven't focused so much on programming and statistics during my undergraduate course, and so would ideally be teaching myself this stuff in my spare time, but is this realistic given the Part III workload (not only this, but the time required to apply to jobs)?

Sorry for all the questions, I really appreciate your time. I haven't managed to make contact with anyone doing part III who wants to go into quant.

 

[cheron_jrm]

Thanks a lot for the response. Could you possibly inform of your background regarding any industry experience you have, and if you've successfully managed to land a job offer for after you graduate? Part III is of course supposed to be pretty difficult - do you find you have enough time to spend on career related things? I, unfortunately, haven't focused so much on programming and statistics during my undergraduate course, and so would ideally be teaching myself this stuff in my spare time, but is this realistic given the Part III workload (not only this, but the time required to apply to jobs)?

Sorry for all the questions, I really appreciate your time. I haven't managed to make contact with anyone doing part III who wants to go into quant.

Sure. I have a "Diplôme d'ingénieur" (French degree equiv. to master level) from Ecole polytechnique, where I studied computational maths, focusing on probability & statistics, along with some programming in java & Python. I had two internships as a quant prior to part III. One in buy side and one in sell side.
I already had a returning offer from the hedge fund when i interned last summer, so I did not have to look for a job during part iii. Though, i had recruiters reaching out on linkedin, mainly for buy side positions.
I think it is realistic to take time learning to code and preparing interviews during part iii. You choose the number of courses you want to do. If you don't want a phd and thus don't need a distinction, you can definitely take less courses. Add to that the fact that there is only two 8week terms of lecture with 1+months between term, and you have plenty of times.
I think what is important to realize is that you'll have a masters in maths, but not in financial maths. So, if you want to be a desk quant and, going to part iii instead of Imperial is a bad move. In the buy side, advanced statistics and probability in general are more sought after for quants (I'm not talking about specific data science positions in BB), and then part III is great.

 

[IIlllIlI]

Sure. I have a "Diplôme d'ingénieur" (French degree equiv. to master level) from Ecole polytechnique, where I studied computational maths, focusing on probability & statistics, along with some programming in java & Python. I had two internships as a quant prior to part III. One in buy side and one in sell side.
I already had a returning offer from the hedge fund when i interned last summer, so I did not have to look for a job during part iii. Though, i had recruiters reaching out on linkedin, mainly for buy side positions.
I think it is realistic to take time learning to code and preparing interviews during part iii. You choose the number of courses you want to do. If you don't want a phd and thus don't need a distinction, you can definitely take less courses. Add to that the fact that there is only two 8week terms of lecture with 1+months between term, and you have plenty of times.
I think what is important to realize is that you'll have a masters in maths, but not in financial maths. So, if you want to be a desk quant and, going to part iii instead of Imperial is a bad move. In the buy side, advanced statistics and probability in general are more sought after for quants (I'm not talking about specific data science positions in BB), and then part III is great.

How come you would say that Stats/prob are more sought after from buy sides? I don’t know enough about the industry yet to agree or disagree - just curious! Edit: like do you mean the buyside interviews are more p&s based? Or the role itself involves more of p&s?

 

[cheron_jrm]

How come you would say that Stats/prob are more sought after from buy sides? I don’t know enough about the industry yet to agree or disagree - just curious! Edit: like do you mean the buyside interviews are more p&s based? Or the role itself involves more of p&s?

I may be wrong, anybody feel free to correct me:

I feel like buy side companies are more keen to hire CS/Stats/ML grads. Amongst the MFE programs with the best buy side placements are Princeton and CMU, which proposes many courses in programming, statistics and ML (the P-quant stuffs, you may want to listen to this Podcast: Princeton’s Carmona on the future of quant education - Risk.net ).

From a Quant Research Job post from DRW : "A degree in a technical discipline with a focus on statistics, machine learning, signal processing, optimization". Though, DRW is more of a quant shop than a traditional hedge fund hiring quants to build tools, but it does not mention financial maths.

From what I've heard at my company too, people do use a lot of statistics, numerical & computational maths, but not much stochal/PDEs.

 

[Phillu]

Thanks a lot for the response. Could you possibly inform of your background regarding any industry experience you have, and if you've successfully managed to land a job offer for after you graduate? Part III is of course supposed to be pretty difficult - do you find you have enough time to spend on career related things? I, unfortunately, haven't focused so much on programming and statistics during my undergraduate course, and so would ideally be teaching myself this stuff in my spare time, but is this realistic given the Part III workload (not only this, but the time required to apply to jobs)?

Sorry for all the questions, I really appreciate your time. I haven't managed to make contact with anyone doing part III who wants to go into quant.

From what you and the part iii guy said I guess you will not be a good suit for part iii. Part iii is completely focused on theory (that’s what Cambridge does! Cambridge statistics means purely mathematical/theoretical statistics and Cambridge applied math means theoretical physics lol). It is true that surviving part iii means you are smart but being smart is a plus while being professional in applied stat/ml/programming are requirements. The part iii guy is from ecole polytechnic which with ens Paris is considered the most rigorous math education in the world (better than Harvard/MIT in my mind), so I’m sure he can do very well in both theoretical and applied aspects and find a satisfactory job in buy side. What you need is not to dig too much on the mathematics side so I think imperial is the best fit. Alternatively, if you go to part iii I guess you will need a secon MSc in financial math or go to do a PhD for a better preparation.

 

[Phillu]

I may be wrong, anybody feel free to correct me:

I feel like buy side companies are more keen to hire CS/Stats/ML grads. Amongst the MFE programs with the best buy side placements are Princeton and CMU, which proposes many courses in programming, statistics and ML (the P-quant stuffs, you may want to listen to this Podcast: Princeton’s Carmona on the future of quant education - Risk.net ).

From a Quant Research Job post from DRW : "A degree in a technical discipline with a focus on statistics, machine learning, signal processing, optimization". Though, DRW is more of a quant shop than a traditional hedge fund hiring quants to build tools, but it does not mention financial maths.

From what I've heard at my company too, people do use a lot of statistics, numerical & computational maths, but not much stochal/PDEs.

It does mention financial math:

• Have completed a Master’s or PhD in a technical discipline with a focus on Statistics, Optimization, Quantitative Finance or related fields
• Proficient Python programming skills with experience exploring large datasets
• Strong analytical and problem-solving skills including a solid foundation of statistics knowledge
• Working knowledge of probability theory, stochastic calculus and numerical algorithms such as finite differences, Monte Carlo simulation, etc.
• Some exposure to Natural Language Processing and/or High-Performance Computing is a plus
• Excellent written and verbal communication skills to report research results as well as methodologies.
  Actually, I think a solid statistics background includes stochastics, and from what I hear, Companies does not use stochastic very much but they like to use it in interviews lol, but I agree with the PDE thing.