If most quants are looking for math/CS majors, what is the point of these MFE/MSF/MSQF programs?

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I've been speaking with many associates/recruiters at prop shops/funds, and it seems like they are mostly looking for CS/math majors, citing "we can teach a code monkey finance but we can't teach a finance guru to code". If so, what is the advantage of a Masters in finance program, over say, a masters in CS/math?
 
I've been speaking with many associates/recruiters at prop shops/funds, and it seems like they are mostly looking for CS/math majors, citing "we can teach a code monkey finance but we can't teach a finance guru to code". If so, what is the advantage of a Masters in finance program, over say, a masters in CS/math?

A Master's in applied math or comp sci with some numerical analysis will probably stand you in better stead than many of these MFE programs (particularly the many bum programs that have mushroomed up during the last fifteen years). Probably be cheaper as well as these MFE programs are unashamedly cash cows for the departments hosting them.

A related question that no-one here asks is: What is the future of quant finance? Does it even have one?
 
I've been speaking with many associates/recruiters at prop shops/funds, and it seems like they are mostly looking for CS/math majors, citing "we can teach a code monkey finance but we can't teach a finance guru to code". If so, what is the advantage of a Masters in finance program, over say, a masters in CS/math?
You should tell those recruiters to have a look at the Quantnet/Baruch C++ courses.
 
A Master's in applied math or comp sci with some numerical analysis will probably stand you in better stead than many of these MFE programs (particularly the many bum programs that have mushroomed up during the last fifteen years). Probably be cheaper as well as these MFE programs are unashamedly cash cows for the departments hosting them.

A related question that no-one here asks is: What is the future of quant finance? Does it even have one?
Computer Science doesn't have enough hard maths contents. This is not news. And numerical analysis is more useful than applied maths (whatever that means..) here.
What do I know.
 
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Computer Science doesn't have enough hard maths contents. This is not news. And numerical analysis is more useful than applied maths (whatever that means..) here.
What do I know.

I would argue there's going to be a shift away from the (so-called) "hard math" -- i.e., stochastic calculus. A few semesters of calculus, some linear algebra, some numerical analysis and PDEs -- this should be ample. Stochastic calculus will be seen as a historical aberration.

But the question of the future of quant finance remains unaddressed. Today's world of finance is arguably a product of the US going off the gold standard in the early '70s. This era seems to be drawing to a close -- the fiat dollar will probably be in serious trouble soon and one consequence of this will (probably) be the end of quant finance as we know it. The new austere (and probably gold-based) world beckoning will probably not allow for frivolities like quant finance.
 
There will be other computationally heavy and data oriented fields to move into, no?

None of the top quant shops like MFEs, so that's not the reason you'd get one, i.e. it is not a path to riches. There are banks and some buy-side firms that have standardized recruiting pipelines with (usually top but not always) MFE programs. I think this is the primary reason you go. Applied math/Stats/CS/ML, you will have to find a way to signal interest in finance and hunt for firms on your own. That being said, imo being at a more quant-focused place like a prop shop or market maker rather than the Point72s and Arrowstreets of the world is a better outcome.
 
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Computer Science doesn't have enough hard maths contents. This is not news. And numerical analysis is more useful than applied maths (whatever that means..) here.
What do I know.

It really depends on the program. Code monkey style not good. Fundamental algorithms, discrete math, linear algebra, calculus, stats, and optimization as it applies to ML, yes. Will get flak for this but I think mathematical maturity and problem-solving ability can be developed without needing crazy PDE and stocal and measure theory (real analysis definitely helps though) especially at this time when all hard math modeling low hanging fruit has been picked and the engineering and production side of things (cloud, GPU hacking, clever feature engineering, visualization tools to get to the heart of the obvious, etc.) is what's adding value. Still need to know enough math, which is still a rare bar to clear it seems...

e.g., this is art. It takes ability to produce something so "applied" and succinct. And I'm saying this having been a math major.
 
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I find the term 'code monkey' to be offensive. What do they call you?
 
... "we can teach a code monkey finance but we can't teach a finance guru to code".

There was a time when people in industry could do both maths and programming (the word 'code' means nothing). Writing reliable software is a skill that takes years to learn.
 
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