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Weighted Ranking of Quant Masters

Hi guys,

I was looking for a good ranking of quant programs and i just found with the list of top ten schools according advancedtrading.com (The Top 10 Quant Schools, According to the Street by Advanced Trading), but without any order, so what I did to rank'em was to take 4 important variables from my point of view to do it. I used the reputation (Rankings) of their respective Engineering, Maths, Business (Finance) and Computer Science Schools. For 1, 2 and 4 I used the USNews ranking, then I searched the top ten that appears in the advancedtrading.com article and I went assigning a value from 1 to 10 according the relative place that they ranked (Less value = better).
For the Business variable I used the Finance ranking by WP Carey School of Business according articles published in Finance since 1990-2007 ( Top 20 Rankings 1990-2007). I assigned this weight to the variables: E(35%), M(35%), B(20%), C(10%).
The summation of all variables for each respective quant program gives me a number (less is better as you can imagine), and these are the results with their scores:

1) Stanford (2.15)
2) Berkeley (3.35)
3) Princeton (4.75)
4) Michigan (5.4)
5) Columbia (5.7)
6) Cornell (5.8)
7) NYU (6.25)
8) Chicago (6.3)
9) Carnegie (6.45)
10) Rutgers (8.85)

Given the details of this ranking formula, you can adjust it as you prefer.......personally I surprised my self with some of them.

Best Regards
Throwing the business ranking in there is debatable. The way engineers think about securities is far different from the way businessmen think about them.

To the engineer, securities are functions and numbers. To the businessman, they are contracts on decisions. The businessman would never be able to see the quantitative subtlety that a good quant does.

As for computer science, once again, an engineer and a computer scientist see programming differently. An engineer uses programming as a tool, and a computer scientist writes programs as an art form. Sometimes, this elegance is unnecessary.
Why I use this 4 variables?.
Engineering, because their fundamental definition of applying technical and scientific knowledge to develop and implement (in this particular case) systems and processes that realize an specific objective based on a specific criteria.

Maths, because obviously it gives the tools to Engineering for an optimal use.

Business, in fact I better had called this variable just Finance, because I think every quant has to know the principles of it and maybe not only the fundamentals but some of advanced topics, otherwise he's unable to research and develop new and original ideas, so personally I think that besides numbers and models a good quant has to understand very well how the financial market works, including its behaviour to make him a full trader, analyst, developer, etc. But I agree with you that is not so relevant as Engineering and Maths, that's why I only gave it a weight of 20% vs 35% for each one E and M.

And the last, Computer Science which I weighted for just 10%, is simply because as mentioned before with Finance variable, is like a plus. As you say the engineer uses programming as a tool, but I think it could be nice to have reputable proffesors in the CS area that gives you even more depth of knowledge to use when you apply "the tool".

Like I said in the original post weigths can be changed according the user point of view and maybe adding more variables. I just tried to bring some order to the advancedtrading.com list.

My best regards
Here's the thing though--the biz schools do not go in depth at all. They touch the surface of everything and then presume your employer trains you.

An engineer can fall asleep on a derivatives course and do well.
Ranking that you've provided is not relevant. A quantitative finance program is strong or not, based on its own curriculum/proffessors, placement record etc.

Computer Science department is not linked to quant finance, same thing with engineering department. You have to do research on specific department.
Where would you rank Baruch MFE with top programs ? - QuantNetwork - Financial Engineering Forum

As a side note, your stats regarding CS grad school are not consistent. You need to be very careful in the criteria considered in the study. Is it research, is it employment record, is it student's satisfaction, is it a broad or specialized program?
Search - Computer Science - Best Graduate Schools - Education - US News and World Report
Some schools do strong research in graphics, others in systems, others in formal.
It matters what is the area of research that you are targeting.

For instance, UNC-Chapel Hill may be exceptional in Graphics, strong in Networking, but may not be the best place in formal ...
Curriculum/Professors, papers on top respective area journals, etc, I think they are already included in the school ranking for each concept. We don't want to count it twice.

Placement Record......mmmmm some doubts about it....I believe placement record is a little questionable since the rate is directly proportional to the university network with the industry and their overall reputation.

Not because a product is expensive (good salaries) or it's been highly demanded for the market, necessarily is the top quality product. Sometimes Marketing works....and very well indeed in some cases.

In this particular ranking I just assigned the school reputation on each field for Engineering, Maths, Finance and CS. Perhaps CS deserves less value e.g 5%, but if you take it out of the equation you would be saying that the use of computer tools is irrelevant for a FE.
My advice is to do more research. You can start reading this forum, talking to alumni or current students, attending sessions.
MFE is a proffessional degree, different criteria from a purely academical Masters.
Also, avoid mixing departments. Only thing that matters is the department which covers this program (e.g. applied math, business school etc).

PS: After some research you will realize that placement record is essential, many factors involved here ...