It's not a very wise investment then, for a candidate, if he really wishes to be a well-rounded quant. Regardless of what area you land a job - a quant developer, a pricing quant, a risk quant, a data scientist.
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Economics and Finance are not enough for a career in Quant Finance
- Thread starter GToul
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It's not a very wise investment then, for a candidate, if he really wishes to be a well-rounded quant. Regardless of what area you land a job - a quant developer, a pricing quant, a risk quant, a data scientist.
Are quants really applying PDEs on their day-to-day tasks? I know that C++ is an extremely useful tool, like any other programming language (especially the open source ones). However, since employers are hiring from these unis how can they “august courses”?
The Quant-Strats team in my bank for example, recently enhanced the engine that generates exposure profiles for equity, rates, FX & credit derivatives etc. So, for example, they made several assumptions about the interest rates, volatility (stochastic), credit spreads based on market dynamics. They modelled the PDEs.
What they're selling is the brand name of their institutions. But in so doing they're arguably debasing that brand name. These degrees are cash cows for these British universities and truth to tell, in this era of reduced state funding, they need the money.
There's a bigger problem lurking in the shadows: British university math and physics education needs to be changed root and stem. The quality of students coming out with "A" levels is not what it was fifty years ago, and the three-year bachelor's program is not enough to impart what a graduate should be knowing today, nor is a one year master's, building on a substandard bachelor's, enough to really be called a graduate program. But this a topic for another thread.
Are members of this team typically math/physics/engineering Ph.D.s?
You're right, they are typically from a math/physics backround - Masters and Ph.D.s.
The standard has dropped dramatically, indeed. Another issue is the focus on research in very narrow and theoretical sub-domains of numerical analysis (for example) to the detriment of its applications in the wider arena.
I am surprised why C++ is not used as much as it should be in the numerate fields in acedemia. Matlab and Python are sad surrogates.
And C# is a well-kept secret.
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I think we all agree that having a Phd in math or physics places you at the top of the quant finance ladder. But does this mean that someone without this kind of background is doomed? Because from what you are saying, this is what I get. There must be people (including myself of course) who although they have studied a less mathematically oriented course, such as economics or finance, but who like math and most importantly like models. So there must be a way in for them too, particularly if they are willing to work hard and learn.
You told me, in one of your earlier posts, that I have to do it like the math/physics undergrads did it; all the way, no shortcuts. But I believe, and please correct me if I am wrong, that among the 20-30 or 40 modules that a math undergrad has, he will actually be applying 20-30% of them in finance. So what I think that would be the ideal solution here is to find a very well structured course (which could last for a year or two it doesnt matter) which walks me through these concepts rather than studying another bachelors. If this course is finally created, I believe that many people wearing my shoes would follow it.
Once again I might not be able to compete them when it comes to certain positions but I hope that I will be able to work with them or in different kind of positions within the same function and learn from them.
These are really good questions and IMO it is incumbent on all stakeholders (especially, the profs and administrators of the various programmes) to engage in this discussion.
Constructive feedback and transparency can play in your favour.
Constructive feedback and transparency can play in your favour.
It's not so much what a quant specifically uses so much as the way he approaches the world (through the prism of PDEs, stoch calculus, linear programming, optimization, and a slew of other math tools that can be called upon at will), a concomitant (yet elusive to define) "mathematical maturity", and an ability to prototype and code fluently in at least one language (preferably C/C++). These one year MFE programs can come nowhere close to giving this. It takes years of solid tech education. For the hard quant stuff employers will probably go for the Ph.D. who's coming from the Jet Propulsion Lab at Caltech. This has all been discussed at length on this forum in years gone by. I'm saying nothing new. For softer stuff, employers may hire MFEs but you'll be contending with an army of other hopefuls.
The probably won't. It's not that they don't know all this but these things cannot be discussed or admitted by them out in the open. They've got to keep the show running, and that depends on eliding over harsh employment realities and singing their siren song of hope.
I guess that this goes for candidates that are not in the industry already. I believe that once in a firm you can work you way through, as I have said before. However, you need to keep learning.
