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Quant rotation

Joined
5/26/19
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3
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11
Hi, I'll be doing an S&T rotational summer analyst program at a BB who includes its trading desk quants within its Sales & Trading division. At the moment I am most interested in trading, but I am interested in quant work as well. I'm a CS major with a solid programming background. Given all of this, would it at all be possible for me to rotate as a desk quant if I manage to talk to the right people, or would I be limited to just trading/sales/structuring? If anyone has experience with this please let me know - thanks!
 
You can always ask and may well succeed, though typically BB quants hire separately, don't take part in rotations, and the bar of entry is higher in terms of degrees (MFE, PhD in a numerate subject). CS is not a particularly useful degree for modelling or desk quant work, though of course most places are not creating that many new models anymore, and have plenty of need for legacy maintenance programming. With that, it's probably more interesting for you to stay within the normal S&T programme, but particularly while in trading do try to talk to the quants and ask them if they could explain whatever it is about the job that you find interesting.
 
i think CS majors can do quant work if they have a good foundation in probability, stats, linear algebra, machine learning, etc. which is possible in a strong CS program.
 
i think CS majors can do quant work if they have a good foundation in probability, stats, linear algebra, machine learning, etc. which is possible in a strong CS program.
CS education tends to focus on a subset of discrete mathematics and applied Algebra. There is a huge branch of mathematics called Analysis (it includes Calculus and much more). The above list (nothing wrong) is not core mathematics as such but applications of maths. Knowing them is no guarantee to learn PDE, stochastics etc. There are no givens. (Analogy: a black belt in judo is no guarantee that you know ju-jutsu .. you have to start as a white belt all over again.)
I would say that numerical analysis is the most important in pricing, hedging etc. In these cases a CS background will not be so useful because you don't know what all those symbols really mean. I think the same challenge holds for the maths behind NN, ML...

And software maintenance is real life.
 
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I wouldn't know since I personally did math, but tons of CS majors from top schools get quant research/trading positions from what I've seen on linkedin. These are mainly on the buy-side so it doesn't really touch the pricing stuff like PDE and stochastics
 
I wouldn't know since I personally did math, but tons of CS majors from top schools get quant research/trading positions from what I've seen on linkedin. These are mainly on the buy-side so it doesn't really touch the pricing stuff like PDE and stochastics
Fair enough. I don't disagree. But the point is each area has/needs its own expertise. If my electrical wires need replacing I don't call a plumber.
PDE has traditionally been the area of ex-Cold War physicists and mathematicians.

But the issue of hard analysis remains IMO. It is more than calculus. At the moment you can use Python libraries without really knowing what's going on inside (black box). But let's say for example you want to write _your_own_ Bayesian network, HMM or XVA hedging application? What skills are needed?

ML is very hot at the moment. It is very interesting to hear Damiano Brigo's views related to the topics here. Each word is carefully chosen and weighed!
Do you start with data (no model needed) or with a model?

 
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Fair enough. I don't disagree. But the point is each area has/needs its own expertise. If my electrical wires need replacing I don't call a plumber.
PDE has traditionally been the area of ex-Cold War physicists and mathematicians.

But the issue of hard analysis remains IMO. It is more than calculus. At the moment you can use Python libraries without really knowing what's going on inside (black box). But let's say for example you want to write _your_own_ Bayesian network, HMM or XVA hedging application? What skills are needed?

ML is very hot at the moment. It is very interesting to hear Damiano Brigo's views related to the topics here. Each word is carefully chosen and weighed!
Do you start with data (no model needed) or with a model?

What textbook or class do you recommend for analysis. I’m free this summer before joining cmu so it maybe something I’ll look into
 
Thanks for the help everyone! This isn't the most related, but in terms of rotations on trading desks I'm hoping to work in FI with products requiring a heavier quantitative background. Would you guys have any suggestions for exact products I should look into (thinking something within derivatives or other illiquid products)? My math background also isn't as strong as I would like, as I haven't taken linear algebra, stochastic calculus, or advanced statistics. What higher level quantitative topics I should really be looking into that would be the most applicable to trading, or should I focus instead on understanding derivatives pricing/options theory?
 
What textbook or class do you recommend for analysis. I’m free this summer before joining cmu so it maybe something I’ll look into
It depends on your requirements and some books are better than others for different areas of analysis.
Two all-round good books

. "An Introduction to Linear Analysis" Kreider, Kuller, Ostberg and Perkins
. "Real Analysis" Haaser and Sullivan

In this case, I think the approach is refreshing and nice reads (they don't go overboard with epsilon and delta stuff).

Some other analysis topics

 
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Another preparation route you can take is forget to learn the math for now, and go the applied route, I.e. something like Options, Futures, and Other Derivatives by Hull, or even better, get some kind of summary or even less deep book about the same. You have no time to learn the math for now in my opinion.
 
Another preparation route you can take is forget to learn the math for now, and go the applied route, I.e. something like Options, Futures, and Other Derivatives by Hull, or even better, get some kind of summary or even less deep book about the same. You have no time to learn the math for now in my opinion.

I'll mention I'm doing my summer analyst stint in 2020, not this summer. I haven't networked for group placement yet either. Does this change my preparation strategy?
 
What textbook or class do you recommend for analysis. I’m free this summer before joining cmu so it maybe something I’ll look into

I used Rudin (PMA) in my undergraduate analysis course, but probably wouldn't recommend it. Maybe consider Understanding Analysis by Abbott instead... same material (at least for what you'd see in a first semester of undergrad analysis, I think), more "motivation". For a course that could earn you college credit, check out UIUC's Elementary Real Analysis provided through their NetMath platform. They'll be adding their more rigorous undergrad analysis section, Real Variables, soon I imagine.
 
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