Best 3 Math Classes
Hey everyone I need some coursework advice:
I'm an economics major in the business school at a large SEC university and I have three free electives which I would like to devote to math. The math requirement for the business school is 123(finite math) & 125(brief cal) or 141(calc 1) & 142(calc 2). My advisor instructed me to take 123/125, which has turned out to be a bad decision because you can't take any other maths without taking 141/142 first. Thus, the first two of my electives will be 141/142 (would be a lot easier if I had just taken these in the first place).
Anyway, I'm afraid I won't have enough coursework to pursue a quantitative finance career, but I want at least some math for finance/accounting in general. So, which of these should I choose as my third (and maybe fourth) elective:
Calc 1
Calc 2
Diff Eq
Linear Alg
Calc 3
I figured you all would be the best people to ask. Thanks
....
Out of those 5, I would rank them as Linear Alg, Diff Eq, Calc 3, Calc 1, Calc 2.
Those 5 wouldn't give you much edge in a quant career, however. Most quant positions are looking for stats, stats, stats, and maybe partial diff eq. As general advice, I have heard the following from multiple sr. level traders at BB & top quant funds: "You can't take enough math." They even said to always choose a math class over a CS class. Here are 5 math classes I would recommend you to get started in your quant career:
Real Analysis is pain in the a**.
As a Math major I took both Business Calculus(brief Calc?) and Calculus one. Calculus one is much more difficult. If you are planing on going into Cal 2 (a weed out class) and above memorize the trig identities they will save you so much time.
edit *I just don't see how you can take Differential Equations with out taking Cal 3 (Multi Variable Calculus) You can easily take linear algebra( easiest math class) with out taking Cal 3 thus in progression I would recommended this:
Cal 1 Cal2 Linear Algebra Cal 3 Differential equations Real Analysis
I hated Linear Algebra, so bad. See if you can take a Data Structures type course through your computer science department. Statistical analysis, & time series would be good as well.
Wall st hack is a fucking idiot. Real analysis has absolutely 0 relevance in finance. If anything take complex analysis. I would rank in this order. As long as you can integrate and take derivatives you don't need too many calc courses.
STOCHASTIC CALCULUS (A MUST BUT YOU NEED STOCHASTIC PROCESs) STOCHASTIC PROCESS (but you need linear algebra and probability for pre reqs) I think you can get by without a full semester of linear algebra if you master concepts on matrix applications and eigan values. PROBABILITY MATHEMATICAL STATISTICS (A CLEAR DIFFERENCE BETWEEN STATS) PARTIAL DIFF EQ (OR TAKE PARTIAL DIFF EQ WITH STOCHASTIC METHODS) COMBINATORICS (WITH GRAPH THEORY) AND A BUNCH OF COMP SCI and FINANCIAL ENGINEERING COURSES
*Linear Algebra is actually pretty difficult. Harder than Multi Variable Calc.
How can you understand probability without real analysis? Though unless you are going hardcore math it's pretty useless.
probability calculus linear algebra statistical mathematics regression analysis econometrics stochastic calculus
Calc 1 - 3 are good courses. Linear Algebra has a lot of application to probability and statistics.
Differential Equations is where you start to draw the line between people who are mathematically apt and people who are ascending towards quantdom. It's overkill if you want to do mainstay trading, but essential if you want to be a geek.
If IBD is your bag, then anything beyond the bare requirements for your graduation is a waste of time. Though any undergrad economics track worth it's salt should require at least Calc 2 (multivariable).
from those you listed, defly take linear algebra. actually take linear algebra even if you dont get into finance. the marginal benefit is so high, you cant miss that class. if you can find, take a stochastic calculus class, probability class and defly start learning programming asap. If you will do quant finance later on, programming will be 80% of what you do.
I agree with dipset, but to accelerate your progress can you take the clep exams for the calculus and pass, should clear you to take the other three.
It really depends on what what kind of a job you want.
Real analysis (Calc 3?) is a very important stepping stone to Stochastic Calculus, which is the key to derivatives pricing. Anything that covers Multi variable calculus (double/triple integrals, optimization, etc) will be very helpful. If you want to be a trader and require a really solid understanding of BSM this and a probability course is a must.
Linear and Diff are more applicable to the quants/nerds who actually build the pricing models - not possible unless you get a MFE/PhD later. For a foundation I'd pick Linear over Diff because analytical PDE methods are pretty "old school".. Hands on implementation of numerical methods (eg cholesky for Linear, finite difference for Diff) would also be a big plus.
And of course if you're headed for IBD you'll only need + - and *. No / necessary.
I am a graduating highschool senior going to University of Illinois next year, majoring in applied math. I am wondering which path would be more beneficial to working in ibank or analyst: graduating in three years, double major w/ finance or econ in 4 years, or transfer to a "target" school? thanks
urbuddy -
1) Illinois IS a target school for many banks. 2) no one gives a flying fuck if you graduate in three years 3) math expertise gives you zero advantage in M&A (OP was talking about HFs, but seems like you're talking about M&A) 4) Take some econ classes, but you needn't go overboard 5) TAKE ACCOUNTING CLASSES!
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