Comment by kwant_kiddo
3 years ago
During my university studies, I found it surprising that although some topics from advanced courses might be applicable in certain jobs like at Jane Street, interviews often emphasised the fundamentals and understanding of basic concepts such as basic probability theory, rather than some specialised knowledge in Lie processes.
If you look through this PDF it does not even cover a 1.semester course in probability theory from a bachelors degree in CS/math.
I always go back to this lecture series to brush up my fundaments. https://projects.iq.harvard.edu/stat110/youtube
Not Lie processes (are you referring to Lévy?), but stochastic calculus in general, which requires a strong intuition for differential equations, calculus, and statistics. Quantitative finance heavily favor those with a background in the physical sciences rather than discrete math like CS.
That is curious. Could you elaborate or point me to some sources, I would like to investigate that relationship further. I remember Jim Simmons saying that the Renaissance fund employs many physicist PhDs and other kinds of scientists. I thought they were there because of their specialisation but perhaps the reason is what you explained above or both
Physicists are popular because they deal with uncertainty and complex models across the time domain, which is another description of markets. When you zoom out far enough, a fluid dynamicist and a market making quant are not that different.
If you want books about trading mathematics and interviews in general, the green book (practical guide to quant finance interviews by Zhou) is the usual go-to. Falcon's Heard On the Street is another classic. Note both of these focus on generic interviews (the quant equivalent of leetcoding) usually for recruiting fresh grads directly out of school. You can probably skip some steps if you have the work experience or know the right people at certain funds.
If you want actual books on trading and modeling, that's another topic entirely.
Figure out which area specifically you are interested in: https://teddit.net/r/wallstreetbets/comments/kcs4xy/what_qua...
If you want an autobiography, Emanuel Derman's My Life as a Quant is well-regarded. I have never read it myself but Amazon has often recommended me The Physics of Wall Street.
yes I meant Lévy I don't really know what went through my head.
I also have to say that you don't need to have a strong intuition for differential equations even through they are very related. Stochastic calculus can be studied entirely in its own right.
And with respect to quantitative finance my experience is that while a candidate knowing about or having coursework in stochastic calculus is certainly relevant its not favourable.
This also depends on the exact job right, if you have to be pricing XVa products then you better have know Girsanov, Ito and what have you =)
I second this. The fundamentals take you far, and Joe Blitzstein has fantastic material.
Slightly off topic, but how do you feel about his “story proofs”? They were the one part of his lectures that never really clicked with me, but I never talked to anyone else about it.
Readers, if you want a great into to probability co-authored by Joe Blitzstein, see https://stat110.net/.
Why can't I download the PDF?
I enjoyed them - I think it shows how you can make a (relatively) rigorous, yet intuitive, argument that does not necessarily have all of the trappings/wall decoration of traditional proofs. The art is noticing when the story is complete vs. when it is papering over an important mathematical aspect.
I took the course in person, so it might have been more understandable in that context.
Me too - particularly when the story proof was more concise than the algebraic proof, or hinted at the deeper reason as to why something must be true. I remember them better too.
I heard they try to hire for aptitude/talent. The sophisticated stuff they will teach you if you’re hired.
This is similar to how math Olympiad students are picked, most questions involve combinatorics and Euclidean geometry instead of advanced calculus, as anyone can understand a basic counting problem, but it’d take a few semesters to define the terms in a typical calculus problem.
Although Olympiad is only counting, there is considerable prep and practice that goes into it.
That’s true. I meant (almost) everyone can understand the ‘statement’ of Olympiad-level counting problems, but of course solving them is another issue.
I heard convex optimiztion techniques are widely used as well, is that true?
Yes, especially in, but limited to, portfolio construction. Check out the mosek portfolio construction cookbook.
Yes. I worked on convex optimization in trading (deeply involved with fine-tuning, constraint selection, utility function construction, etc.).