Which Math Course, Calc 2, Stats 2 or Linear Algebra?

I am trying to figure out which of those courses would be best to prepare me for a general MSF degree (I only have calc 1 and stats 1 now) I am not sure which way to go, leaning towards stats because it seems more practical and utilizes software that could come in handy. Please let me know if you have any other suggestions. Thank you.

 
Best Response

Pretty much every serious MSF program requires calculus / linear algebra / statistics / real analysis, so take as many of those as you can. Even if the program doesn't formally require so much math, math fluency always helps. In order of priority, and pretty much in sequence:

  1. Calculus and linear algebra (sets, sequences, limits, subspaces, integrals, differential forms)
  2. Statistics (where you use integrals but not measure theory)
  3. Real analysis (Lebesgue integral, Lp space, approximation theorms)
  4. Probability theory (sigma fields, Kolmogorov conditioning, convergence, martingales)
  5. Time series (stochastic processes, Brownian motion, functional central limit theorms)

The further you get along the sequence, the more you will be able to spend time learning finance rather than math, which will reflect well for future interviews. Pick up Matlab along the way and you'll be solid.

 
Notepad:
Pretty much every serious MSF program requires calculus / linear algebra / statistics / real analysis, so take as many of those as you can. Even if the program doesn't formally require so much math, math fluency always helps. In order of priority, and pretty much in sequence:
  1. Calculus and linear algebra (sets, sequences, limits, subspaces, integrals, differential forms)
  2. Statistics (where you use integrals but not measure theory)
  3. Real analysis (Lebesgue integral, Lp space, approximation theorms)
  4. Probability theory (sigma fields, Kolmogorov conditioning, convergence, martingales)
  5. Time series (stochastic processes, Brownian motion, functional central limit theorms)

The further you get along the sequence, the more you will be able to spend time learning finance rather than math, which will reflect well for future interviews. Pick up Matlab along the way and you'll be solid.

Good list. I would throw in a PDE course if time permits. (Useful when you get to feynman-kac representations)

-MBP
 
euroazn:
Hey notepad - out of curiosity, why is time series so low and real analysis so high?

Because one learns measure theory in real analysis, and probability is basically just measure theory. Probability is a pre-req for stochastic calculus (which I think is what he meant by time series), which is used in every part of derivatives pricing.

-MBP
 
euroazn:
Hey notepad - out of curiosity, why is time series so low and real analysis so high?

It's true that with basically no math or stats, you can go ahead and take a class that uses something like Hamilton to learn the classical theory, but you'll have absolutely no idea how to handle anything non-classical. The usual theory simply fails. Given the current industry focus on fat tails, measurement in the presence of microstructure noise, non-normality, and other non-standard setups, I think it's worth building up the math foundations to take a more advanced course instead.

 
Notepad:
euroazn:
Hey notepad - out of curiosity, why is time series so low and real analysis so high?

It's true that with basically no math or stats, you can go ahead and take a class that uses something like Hamilton to learn the classical theory, but you'll have absolutely no idea how to handle anything non-classical. The usual theory simply fails. Given the current industry focus on fat tails, measurement in the presence of microstructure noise, non-normality, and other non-standard setups, I think it's worth building up the math foundations to take a more advanced course instead.

Hm. Gotcha. Might have to reconsider the classes I was planning to take then! Thanks!
 
TW Pepper:
At the bare minimum, calc 2, linear algebra, and a calc based prob/stats class. If you have time, then diff eq and calc 3 and an analysis course.

The people who took just the bare minimum requirements got absolutely slaughtered in my MFE.

-MBP
 
blastoise:
i don't understand how you can take linear algebra with out cal 2.......
It's the other way around bro. You take linear algebra, and then you can analyze multivariable calculus properly. Remmember the second derivative test? That's just a determinant. Extended for higher derivatives also.

And then there's manifolds :3

 

Thank you for all the posts & suggestions. I am not going the quant route, but as TW Pepper said, the MSF. I will have only one semester to take the course/s and I am still not sure which of the 3 courses listed I should take. Only keeping in mind the MSF, which course would I take away the most applicable information/skills I would use during my course of study?

 

I agree that Calc 2 would be much more difficult to learn on your own than linear algebra.

As to original question - I say take stats. WAY more applicable than linear algebra - you will not be using linear algebra in an MSF, but an understanding of stats will go a long way. Probably need Calc 2 for a decent stats course though... but any stats would be beneficial if you have no experience in it at all.

 

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