Can you tell everyone here what Galois theory and number theory have to do with quant finance instead of engaging in idle and worthless ad hominems?
argumentum ad hominem is bijective in nature: take a second to think about that one. the irony is that you resorted to ad hominem. i provided solid, unspectacular advice and added in my own personal view (perhaps unconventional, should i shut up?) and you attacked, like any true fool.
there is nothing specific about those galois theory or number theory that will make you a good quant. the best quants that i have worked with have very 'different' backgrounds. the only condition one should follow is that they should study a subject quantitative in nature and should show an interest in finance. that is sufficient and necessary for being a good quant. nothing else.
one should not be an idiot savant -> different topics provide different challenges -> you learn to solve different challenges. you get a bigger picture of what it means to think quantitatively. this is the kind of attitude that a lot of people will never have because they don't have the balls to try different things. it is called discipline. to find someone who can just tap into different topics (that are quantitative in nature), understand the challenges in those topics and find a way to solve them ... -> you have someone who sees the whole picture.
i am tempted to quote (the british mathematician) G. Hardy's thoughts on number theory -> his love for it was dual to its non applicability. of course, we know how that turned out. don't be a fool like Hardy, use your brain. do you think knowledge of PDE's or whatever topic XYZ is
really going to make that much of a difference to working as a quant? the answer is no. it doesn't matter you really study, as long as it is quantitative in nature. that being said, some topics do help more than others.
let us put some icing on the cake: here is an application of number theory to quant finance:
a lot of practitioners and researchers are interested in infinitely divisible distributions. they correspond to levy processes. will you be so stupid as to deny that levy processes have applications in finance? one can generalise infinite divisibility to probability measures by use of characteristic functions. consider the riemann zeta function and the hypothesis that the zeros of this function lie on the singleton u=0.5 of the critical strip 0 <= u <= 1. one can show that the quotient of two riemann zeta functions is the characteristic function of an infinite divisible probability measure. now, one can start delving a little deeper about the number theoretic aspects of infinite divisibility by looking at said hypothesis.
you wouldn't learn things like that if you were the kind of (moron) person whom didn't try new things that are sometimes completely unrelated to quant finance. in the end, the path is always the same: you form a bigger picture.
