Atleast 2/3rd of the research published in some form of empirical work. ...
... a PhD Math student will have the opportunity to do research with a professor in the finance department...that is a really far stretch. It almost never happens...
Hey Joy Pathak. So I was reading your reply and correct me if i am wrong, the conclusion I seem to make is that these highly scientific highly advance mathematical techniques aka the ones I mentioned, Machine Learning, PDE, Signal Processing, are only present in the corporate firms such as DE Shaw, Renaissance and Winton Capital. From your post, it seems like these breed of quants have no place in the university. They need a Math PhD but can't find work at the Finance department. And maybe they take some finance classes but they are highly empirical. No room for fancy analysis there.
Thinking about it. It seems to be true thereby concluding that the path to those firm is very narrow confirming the common mandate that "scientist are going to Wall St". If such a method by some guy in the Electrical Engineering department found a way to make tons of money through automated trading, he'll probably only publish the scientific part and not the application part. Why? Not much use having a finance related application in the IEEE or ACM correct.
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If you are aiming for finance, do a PhD in a related area -- such as the numerical analysis of PDEs.
This seems to clear up a misconception which I also had early. I mean I read interviews saying people with a PhD in number theory going to finance because all those firms want the 'really smart people'. But then I thought to myself, PDEs seem SO MUCH closer to finance than number theory.
But may I enquire a little further. How much do you think a dissertation in PDE, and I mean the content in the dissertation itself, has applications in finance. I know it definitely varies depending on the title. Can there be a case where a guy, like me, spends 3 years writing a dissertation such that it has FULL applicability in quant trading. He can take the concept, code and run the algorithm.
Yes, PhD in PDE aid the learning. But can a revolutionary idea, deed worthy by faculty in the Math department, takes it origins from problems in finance. Because if such problems exist, the ones that come from finance but cast in math, I'm SURE to fire all abstract ideas - functional analysis, topology(?), differential geometry - at it. Just makes me happy knowing those otherwise unrelated classes have its uses later.