A voice of realism needed!

[SailingQuant]

Hello everyone!

To give some backstory, I am a successful systems engineer by trade (3 years out of college) but I have been trying to transition into a career in quantitative finance. I took the GRE and came out very well (163 verbal 167 quant) and as such my mind got set on all these top tier programs (MFE and similar). I need someone to tell me if it is worth even applying to those schools , or if my background just won't make the cut.

Profile:
GRE: 163 verbal 167 quant
BS in electrical engineering from a florida university.
GPA:3.8
Relevant courses:
Calculus I/II/III
Differential Equations
Engineering Statistics
Engineering Analysis (EE version of matrix algebra/ linear)
Random Variables and Stochastic Processes- graduate level from Purdue University

Probably irrelevant but additional computationally intensive frequency domain courses:
Linear Systems Analysis
Digital Signal Processing

Programming: Matlab, C/C++, and some Java

Work experience: Systems Engineer for 5 yrs (2 yrs internship). Primary role is data analytics/algorithm development/analysis tool development. Not finance related but again computationally intensive. Lots of work with 3D covariances and various rotations/translations.

So where I need a realistic perspective is do you feel it is worth applying to those top tier schools? (Columbia, CMU, U of Chicago, NYU etc.)

Are MFE's still worth while from lesser schools?(BU, GTech)

Do I even have what it takes to get into a quant program?

I don't mind the application process but I wouldn't want to spend the money if there is very little to no shot of actually getting in.

I have been reading these boards long enough to know that you all get a lot of these, so any recommendations and opinions are greatly appreciated!

Thanks

 

[bigbadwolf]

Some real analysis would be useful. Think of real analysis as calc but based on properties of the real numbers rather than geometric or physical intuition. A course in numerical analysis would also come in handy. Otherwise I can´t see anything lacking.

 

[SailingQuant]

Thank you for your reply!

Do you feel the lack of actual course work in these areas would disqualify me from the MFE programs? Or could it be self taught?( I taught myself calc I/II over a highschool summer so I could take calc based physics, so self learning shouldn't be an issue)

Thanks again for the input!

 

[bigbadwolf]

Thank you for your reply!

Do you feel the lack of actual course work in these areas would disqualify me from the MFE programs? Or could it be self taught?( I taught myself calc I/II over a highschool summer so I could take calc based physics, so self learning shouldn't be an issue)

Thanks again for the input!

It's all self-teachable. If you attend a formal course you still usually teach yourself -- it's not as if you're getting personalised one-on-one attention, and the lectures can often be dull, uninspired, or even indecipherable. Often the only advantage of a formal course is that it imposes the discipline of a forced march on a student.

For an autodidact the only really hurdle is to stumble serendipitously across the right texts. There are a number of such books for real analysis (which I can't name as I'm currently separated from my library by a few thousand miles). Just remember the key motivation for real analysis: initially it's the same topics as calc except on the rigorous foundation of the structure of the real numbers. Thus, for example, the intermediate value theorem is proved rigorously; the derivative and integral (Riemann or Lebesgue) are defined without reference to tangent lines, rates of change or areas; and the mean value theorem is proved rigorously. With regard to why we bother with rigor for this subject matter, it's because it allows us to extend the theory to areas where intuition leads us astray.

 

[CasanovaJ]

Why do you want to switch to careers-- what background/experience do you have with finance?

 

[SailingQuant]

Well as an engineer what i most loved most was the analysis tool/modeling and simulation development, but as time progressed my abilities were getting throttled by the limited need. What I love most is mathematics, I've taught calculus through DE because I enjoy it so much. The quant career seemed like a perfect fit for my love of programming and math, the finance aspect is the icing on the cake! Background is limited to simple cost account management finance wise. when I was looking at jobs over the last year with matlab development, all of the quant jobs were fascinating with their application to the financial world. So I did more research and decided it was a worthy endeavor. Make sense?