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Advice for a New Member

Hi Everyone,

I am a mathematics and computer science major at Cornell entering my junior year. I have recently become interested in quantitative finance because of its greater use of deeper math than tech. I have had classes in algorithms, theoretical computer science, odes, pdes, non-linear dynamics, lin alg , abstract algebra. I have done research in system identification (parameter estimation of linear dynamical systems) and am interested in taking more classes in graduate dynamical systems, pdes, algebraic topology and computational topology(data science bent). I like research and have not stopped becoming curious in new fields of math. I have also become very interested in markets and am looking to learn more.

I have a few questions about coursework, internships and general advice.

First, should I take a broader distribution of classes ie. more stats, machine learning, econ, finance classes or is focusing on deep mathematics just as valuable.

Second, I have a relatively low GPA namely a 3.36. Much of this was caused by overloading on senior level math and cs courses last semester. I am confident though that I can pull As in our senior level math and cs courses given a light enough semester, especially if I mix econ and aem classes. On the other hand, I view this a little bit as not challenging myself enough and getting my money's worth. Should I take easier classes some and ensure a better GPA or take more challenging classes that will increase my exposure/skill?

Third, I am currently split as to whether I would like to go into industry or graduate school. My family is not that well off so I feel obligated to go to industry. However, I feel that graduate school would be more stimulating intellectually. My question is then whether you find quantitative finance to be intellectually rewarding and whether there are regrets about going/or not going to graduate school.

Fourth, I have always wanted to work in a national lab doing research(FERMI or LLNL) and partially looking into doing this next summer and not doing finance. How important is to have a technical finance internship versus some other internship (scientific computing or physics data analysis).

Thanks for your help and advice!
 
1) In quantitative finance you have to learn a lot (much more than a normal individual can ;))
The only way is to learn the fundamentals to than you can further dwelt in any (sub)area of your interest and/or professional need.
One example from my own experience: as students, we were to choose between functional analysis and time series. One girl choose time series because "it it highly applied and you never will need functional analysis in real life". However, it was functional analysis that allowed me to understand not just the basic time series models like ARMA (which this girl learnt) but also such advanced models like LSW-processes (https://www.quantnet.com/bookmarks/?type=post&id=179409)

2) no idea, sorry

3) Go to industry! In quantitative finance practice matters much more than a knowledge of yet another theoretically flawless but practically impracticable model, which is used by nobody.
Moreover, if you have enough will, you can work full time and study part-time or by yoursel, specializing in the domain of your interest (as I, for one, did).

4) Yes, try to get to research and if you (likely) get strongly disappointed, don't forget to come back here and frankly tell us your story ;)
 
Hi First, should I take a broader distribution of classes ie. more stats, machine learning, econ, finance classes or is focusing on deep mathematics just as valuable.

If you're set on quant, take those applied classes because they will be very relevant if you eventually decide to do an MFE. The deep math won't really help on a day-to-day basis but like yetanotherquant said, sometimes it will give you an advantage.

Should I take easier classes some and ensure a better GPA or take more challenging classes that will increase my exposure/skill?

Take a mix of the most interesting looking classes and the easiest (but still mildly interesting) classes. Diversify.

My question is then whether you find quantitative finance to be intellectually rewarding and whether there are regrets about going/or not going to graduate school.

Intellectually rewarding - definitely. The MFE is probably the hardest thing academically I have done, especially since I did it while working full time. There were International Math Olympiad winners who were struggling in my program so that really shows you how intense it is. I have no regrets about doing it though.

Fourth, I have always wanted to work in a national lab doing research(FERMI or LLNL) and partially looking into doing this next summer and not doing finance. How important is to have a technical finance internship versus some other internship (scientific computing or physics data analysis).

Doing an internship really helps. Many firms recruit the majority of their new analyst class through the internship program. Since you will be a rising senior next summer, it is the perfect timing to do an internship. There's a good chance your summer employer will offer you a job at the end of the internship (and you won't have to deal with job hunting in your senior year) so choose wisely.
 
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