MS in Mathematics in Finance / MFE
Hey everyone,
So just speculation at this point, but if I ever go back to school it'd likely be for a Master's in something quantitative. The only problem I have is that I became very interested in math very late in my college career (senior year to be exact) and thus have only take up to Calculus II (and some immaterial derivatives, applied econometrics, and stats classes) and I have little to know programming skills (can and have worked on picking up VBA).
Hypothetically if I wanted to go back for an MFE or equivalent, what would be the best way of doing so? I've thought about enrolling in non-degree courses so that I can earn the baseline prerequisites such as linear algebra, more calc/diff equations, and probability, but honestly am not keen on taking out any more loans and dealing with all the admin BS that comes with it. Would it be sufficient to say... take some open courseware classes from MIT and then try to take a competency exam? (Also do well on GRE, etc.)
I will admit, that maybe I'm just not cut out for it. Looking at NYU's program and student roster, most of their resumes are pretty impressive in regards to math.
Again, this is all speculative, but any advice would be greatly appreciated from anyone knowledgeable!
bump!
That's a pretty speedy bump, lol...IlliniProgrammer is probably going to be your best source here, but if by sufficient you mean "able to apply" then I would suggest taking a look at the websites of the schools/programs you're interested in, they should tell you what their application requirements are in terms of math (or if not, call up a few of them). Math isn't too hard, you can definitely just teach yourself if needed.
I know, I can be a little impatient at times. And I was hoping that he could shed a little light on this for me too.
I've looked at most of the websites for schools I think would be worth applying to and most require: multivariable calculus, linear algebra, and probability (don't mention programming, but I'm under the impression that I'd need some).
And I'm just curious to know if I'd have to have "officially" taken these classes to enroll, or if I'd need to take the equivalent of an entrance exam regarding those prerequisites. Also, as I said, I've only taken up to Calculus II so am a little worried about being able to comprehensively learn Calculus III material enough to do well in grad school.
I mean, I can do Calc II questions in general with some review, but if you really want to make something hard, it's pretty easy to just pile more rules and theorems into a simple integral problem to the point where it is very difficult.
So here is the standard Engineering Math Sequence at UIUC. This is what got me into Princeton:
1.) Calc I (Derivatives) 2.) Calc II (Integrals) 3.) Calc III (Multivariable) 4.) Linear Algebra (Invertibility, Eigenvectors, Eigenvalues) 5.) Calculus-Based Probability 6.) Differential Equations
Also highly recommended but not required: Real Analysis (I did not take this, but I wish I had) A low-key stochastic calculus course covering Weiner Integrals, Ito's Lemma, Feynman-Katz, and The Girsanov Theorem. (I did not take this but wish I had.)
A lot of students in the program have more; a few have less, but not that much less.
If you're in NYC, I'd look into taking some evening math classes at Baruch or maybe doing UIUC's netmath program. I'm pretty sure you can do all of the above through UIUC.
I use Calc III almost every day. I use linear algebra almost every day, but I try to avoid it as much as possible. I use probability every day.
I don't use DiffyQs. If there's a class you can cut from this list, it's probably #6. So that leaves you with three required courses, plus one basic programming course. (If you are going for CMU's MSCF, I also recommend data structures and algorithms courses; this is a programming-heavy program, and a lot of the other students will have CS undergrads.)
Thank you! This is still all hypothetical, but I'm considering it more and more each day. I'm in NYC, so looking at schools around here.
I've done #1 & #2 on your list and plan on at some point taking #3-6 at NYU or Baruch sometime down the road as non-degree study. I could probably try and teach myself some real analysis (after doing Calc III); and you seldom use differential equations? I thought Black-Scholes was a PDE? Are their specific areas where certain maths are more useful? I honestly like Calculus stuff the most, so happy to learn more about that.
I'm not completely adverse to programming, however it isn't my desire to become much of a programmer if I don't have to (just the necessary languages for work).
Thanks again, would give you 2 SBs if I could.
Real analysis is the last class in the world I could imagine teaching myself. Unless you have taken a proof heavy math class it is not going to happen. It is one of the classes I took where I didn't understand a thing until the VERY end and I suddenly put it all together and 'got it.' Like I said, I cannot imagine understanding much of it without someone guiding me.
Whoa. What from Calc III are you using every day?
Econ courses- maximize a policy maker's object function with respect to interest rate. Theoretically you can just plug and chug, but calculating the partial derivative of inflation with respect to rate and partial of unemployment with respect to rate makes everything a lot easier.
Stats courses- calculating the MLE for a distribution or a regression.
The website I'm building- calculating marginal Sharpes.
Econometrics.
The integral and polar notation conversion stuff is pretty rare, but you are calculating gradients and setting them to zero 24/7.
I think I did more partial derivatives during my first month at school than I did in five years in industry or in my original Calc III course.
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