Honours in AP math for Quantitive finance?

[Acorns844]

Should i do honours in Applied Mathematics , Computer Science , Operations Research or Financial Modelling ?

I am in third (final)year in Bsc Applied mathematics and Computer Science , i want to get into something finance in a bank or investment firm
so i want to know what is the best honours degree i could do to get into that field or at the very least something data science related.

any advice ? I have no gotten a graduate program as yet so im looking to do honours should a graduate role or internship not come up.

 

[Jehosefat]

Of the ones you have listed, I would avoid Comp Sci Honours if you are trying to get into finance but other than that, go with what you are most interested in.
Getting in to grad programs and the like are about: (most of these specific details are for quants grad programs because that's what I'm involved in)

1. Having a degree in the appropriate subject (math, stats, applied maths, econometrics, actuarial science etc. for quants grad programs; can be a bit broader for general banking grad programs)
2. Make sure your marks are good enough to get you an interview
3. Demonstrate interest in the industry (e.g. for banking ensure you you know about Basel III, bank specific IFRS regulations (IFRS9) etc., for investments, show that you have invested yourself or researched companies or taken part in stock market challenges etc.)
4. Most of the grad program interview processes will have case studies/problem solving questions so having the ability to think laterally, reason through problems, and come up with reasonable answers to questions that you have never seen before is key

 

[cguy]

I would say that applied maths is most important - it’s the core work/concepts. Assuming you’ve also got some undergrad stats, that side of things will be a reasonably easy independent study.

Financial modeling courses can be a bit dated. Depending on what you end up doing, understanding the maths behind AI is also good for any types of modern forecasting work being done.

Almost everything you do will be via code (whether written by an agent or not), so it’s good to have strong coding skills too (although for the purposes of studying, a lot of the CS hons will be less relevant (and easier to pick up in the job) than mathematical maturity).

 

[Acorns844]

I would say that applied maths is most important - it’s the core work/concepts. Assuming you’ve also got some undergrad stats, that side of things will be a reasonably easy independent study.

Financial modeling courses can be a bit dated. Depending on what you end up doing, understanding the maths behind AI is also good for any types of modern forecasting work being done.

Almost everything you do will be via code (whether written by an agent or not), so it’s good to have strong coding skills too (although for the purposes of studying, a lot of the CS hons will be less relevant (and easier to pick up in the job) than mathematical maturity).

So you would say Applied Mathematics honours is better over computer science in this case
maybe Applied math is less saturated so it would be advantageous

 

[Scooby_Doo]

AI scares me for all of those subjects.

 

[cguy]

So you would say Applied Mathematics honours is better over computer science in this case
maybe Applied math is less saturated so it would be advantageous

Yes, it’s better, but not due to saturation, rather to understand the material for quantitative finance, advanced applied maths skills are just better. It is likely not going to actually be a specific topic in your app maths honours course that is directly relevant, but rather the general improved mathematical literacy and practice.

You’re likely going to be writing/agenting code a lot, but it’s easier to improve on this in the job (especially if you already have a major in CS) than it is to gain the mathematical muscle.

I’ve been in QF for about 17 years now (in the US). Most of the QRs have PhDs (perhaps a handful of masters degrees) in app-math/physics/stats/pure-maths. A few have engineering or mathematical CS backgrounds.

 

[cguy]

AI scares me for all of those subjects.

To build anything that pushes a boundary, you’re going to have to know what the AI is doings, as well as how. When it reports results, stats, etc., you’re also going to need to know how to interpret them.

While there has been a major shift in how we work, groking the domain has become more important, and the mechanics of implementation much less so. This has made the right education even more important. I haven’t seen a fall off in this (in terms of hiring), but yeah, people whose job it was to implement things thousands of other people had done, but with a tweak here and there are in trouble.

Similarly, doing mechanical maths is now super easy (you say what you want to compute and it computes it), no more implementing of matrix algorithms, or hand writing Eigen code, but you still need to know what to ask it for, what the answer means, how reliable it is, and how to set up your processes so that you get real answers. It’s still far from capable of pushing most boundaries by itself.

 

[Jan van Riebeeckstad]

 

[B-1]

So you would say Applied Mathematics honours is better over computer science in this case
maybe Applied math is less saturated so it would be advantageous

Math is more generic, still applicable and will be impressive when someone looks at your CV 20 years from now.

You can do a few short courses and certifications if you want your CV to be more focussed.