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COMPARE A hard decision: UCL CF vs Imperial MathFin

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1/13/23
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Hi guys, I currently have to choose between two one-year study exchange programs and I‘m kind of struggling to make a decision, would be awesome to get some opinions.

My background: BSc Mathematics from TU Berlin, was awarded a price for outstdanding achievements. Currently doing a MSc in maths and statistics, focusing on mathematical finance (very theory and probability focussed)

My exchange opportunities:

1) MSci Mathematics (Year 4 at postgraduate level) of Imperial College London (taking courses in ML, stochastic simulation, computational PDEs and statistics)

2) MSc Financial Mathematics (1 full year) at University College London (courses in Computational Finance, Financial Numerics, a C++ course, Statistics of algorithmic trading)

My goal: Doing a PhD in mathematical finance, maybe connected to ML. Later on either staying in academia or doing research and development at a trading company.

It feels like UCL is the obvious choice, but Imperial has a more outstanding reputation and offers good courses in ML, unfortunately offering almost no courses with a direct focus on financial applications (the courses are more theoretical).

What would you guys choose?:giggle:
 
Which coursework interests you more? Because that is what I would choose. Also you are doing a PhD down the road - find which university has faculty that you would want to research under. Don't concern yourself with hypothetical job offers that would be 5-7 years down the road - you still have to get through an MS/PhD first. Check that box and then move to the next goal. Don't overthink it, you can find a path to quant with either option.
 
I think there are two useful perspectives here.

(1) Your BSc and MSc are both mathematics-oriented, and from how you describe it sounds like your current MSc is giving you a formal background in probability and stochastic analysis analogous to what you would see in 1st year PhD coursework. This makes the case for doing the UCL program as it will expose you to an "applications" oriented approach to quantitative finance and also will force you to start programming frequently instead of just writing proofs. This I think has the ability to couple well with your maths background and can allow you to hone your research interests in mathematical finance prior to doing a PhD. Additionally, since UCL's coursework will likely be comparatively less time-consuming, you will potentially have opportunities (not sure how this works in the UK) to work as a research assistant.

(2) Your BSc and MSc are both mathematics-oriented, therefore, assuming you are a strong student, much of the material covered in UCL's coursework is self-learnable. The ICL MSc will further expose you to additional formalism, given you mentioned the courses are more theoretical than UCL, and while there are no quant finance application courses, there are several books applying the subjects you will learn to problems in finance and so it is not as if the curriculum is totally isolated from quant finance.
 
I think there are two useful perspectives here.

(1) Your BSc and MSc are both mathematics-oriented, and from how you describe it sounds like your current MSc is giving you a formal background in probability and stochastic analysis analogous to what you would see in 1st year PhD coursework. This makes the case for doing the UCL program as it will expose you to an "applications" oriented approach to quantitative finance and also will force you to start programming frequently instead of just writing proofs. This I think has the ability to couple well with your maths background and can allow you to hone your research interests in mathematical finance prior to doing a PhD. Additionally, since UCL's coursework will likely be comparatively less time-consuming, you will potentially have opportunities (not sure how this works in the UK) to work as a research assistant.

(2) Your BSc and MSc are both mathematics-oriented, therefore, assuming you are a strong student, much of the material covered in UCL's coursework is self-learnable. The ICL MSc will further expose you to additional formalism, given you mentioned the courses are more theoretical than UCL, and while there are no quant finance application courses, there are several books applying the subjects you will learn to problems in finance and so it is not as if the curriculum is totally isolated from quant finance.
Hi, just to update you. I was now accepted for Imperial. Thank you for taking the time to write an answer :)
 
Nice. I think @TheCheshireCat is going to Imperial as well according to the Tracker.

Yes, I am currently an MSci Mathematics student here (in my fourth year). Then rejoining Imperial in October on the MSc MathFin course. You can reach out to me about what modules to take (I have taken all the courses you have mentioned, although there are a few statistics modules I did not take) @unzial .

Edit: Also, I disagree that there are no courses with direct financial applications. We have: Introduction To Option Pricing, Stochastic Differential Equations In Financial Modelling, and Consumer Credit Risk Modelling.

Also, you can take modules from the computing department too, which offers: Decentralised Finance, and Computational Finance. I did not take it, but I heard the latter covered black scholes, and portfolio optimization methods.
 
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Yes, I am currently an MSci Mathematics student here (in my fourth year). Then rejoining Imperial in October on the MSc MathFin course. You can reach out to me about what modules to take (I have taken all the courses you have mentioned, although there are a few statistics modules I did not take) @unzial .

Edit: Also, I disagree that there are no courses with direct financial applications. We have: Introduction To Option Pricing, Stochastic Differential Equations In Financial Modelling, and Consumer Credit Risk Modelling.

Also, you can take modules from the computing department too, which offers: Decentralised Finance, and Computational Finance. I did not take it, but I heard the latter covered black scholes, and portfolio optimization methods.
We have the first review of the Imperial program :)
I hope more are coming.
 
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