I remember going through that Pdf when I was interviewing with them. Very helpful stuff. I feel like I learned more about statistics while going through hundreds of Jane Street interview questions than I did during my university studies.
Probability and Markets [pdf]
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Re: Probability and Markets [pdf]
#42The first section on randomness seems to imply that all you need to know is information. That if you knew all the data about the weather that you could predict the weather. I think it's more complicated than that. Even if you knew the position, type, and velocity of every molecule of the atmosphere at a given moment you would still need a model that explains how they interact over time in order to predict the future.…
> Even if you knew the position, type, and velocity of every molecule of the atmosphere at a given moment you would still need a model that explains how they interact over time in order to predict the future. So, I'm not sure that actually is a knowable unknown because that assumes there is a model that can be made in addition to the information. Maybe the weather is chaotic.
It is, but that doesn't mean you couldn't predict it with perfect information. A chaotic system is roughly speaking one that is
- sensitive to initial conditions, in the sense that the distance between nearby trajectories in phase space grows as e^{l*t} for time t and some positive number l
- mixing, meaning that given any two open sets in phase space X and Y there's at least one trajectory from a point in X to a point in Y.
and so if you have any error bounds at all on your measurement of the initial state (which of course you always do) then you can't predict where it ends up in the long term. But there are plenty of chaotic systems for which exact numerical computations are quite simple. The logistic map x_{n+1} = rx_{n}*(1-x_{n}) for instance, is chaotic for many values of r.
Re: Probability and Markets [pdf]
#43Honestly I expected it to go over far more advanced topics than these, most of these are covered in the last year of high school over here.
Turns out trading doesn't require that much advanced math
Re: Probability and Markets [pdf]
#44What was the probability that one of JaneStreet’s alumni, Sam Bankman Fried, would use JaneStreet’s brand name to build up credibility and then pull off the biggest ponzi scheme in human history?
The fact that JaneStreet hired both SBF and Caroline shows their interview process has a few flaws.
Why? Maybe they were good employees? Just because they did something bad after really isn't thst relevant.
Re: Probability and Markets [pdf]
#45That seems easy, then why is getting a job there so hard? the pdf is undergrad level. it is covered in any elementary stat or probability book. I guess you have to do it on the fly or something. or have a good intuition for estimating probability when the formula is too cumbersome.
Re: Probability and Markets [pdf]
#46Earlier quoted context omitted.
The fact that JaneStreet hired both SBF and Caroline shows their interview process has a few flaws.
Why? Maybe they were good employees? Just because they did something bad after really isn't thst relevant.
It shows JS doesn’t scan for morality or ethics or judgement.
Re: Probability and Markets [pdf]
#47This seems like a sub-optimal way of finding top talent, even though the results still speak for themselves. Obviously Jane Street has had a lot of success using brain teasers to screen for talent.
If i were a hedge fund recruiter, here is what I would do:
Go on /r/ wallstreetbets and find guys who consistently are pulling huge $ like this guy:
https://old.reddit.com/r/wallstreetbets/comments/14a9xyi/11m...
Send a DM job offer to all of them, 7 figures plus performance comp , or at least an interview that will be paid anyway, so as to not waste the recipient's time.
Why ask brain teasers to try to find skills that correlate with trading when you can just pick out the best traders who already have demonstrable skill? that is how sports recruiting works. they find the people who can play the sport at best level.
Re: Probability and Markets [pdf]
#48During 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 theo…
I heard convex optimiztion techniques are widely used as well, is that true?
Re: Probability and Markets [pdf]
#49For the experts in the thread complaining about the simplicity of the excellent introductory text in the OP, here's an exciting reading for you: Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications by Nassim Nicholas Taleb https://www.amazon.com/Statistical-Consequences-Fat-Tails-Pr... Beware that it may be way more advanced than what you'd expect though.
would you recommend any books/resources before jumping straight to this? Thanks!
Anything that would help build a strong probability theory background.
Assuming you have some freshman-college math literacy, here are a few great introductory books to Probability theory:
Introduction To Probability by D. Bertsekas & J. Tsitsiklis
Elementary Probability Theory: With Stochastic Processes and an Introduction to Mathematical Finance by K. L. Chung & F. AitSahlia
An Introduction to Probability Theory and Its Applications Vol. 1 by W. Feller
I'm sure there are some great video lectures on the subject as well, but unfortunately I can't point you to any relevant material since textbooks is what I used when I was in college. But if I had to guess, the latest relevant MIT OCW course that has video lectures available would be sufficient.
Re: Probability and Markets [pdf]
#50For the experts in the thread complaining about the simplicity of the excellent introductory text in the OP, here's an exciting reading for you: Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications by Nassim Nicholas Taleb https://www.amazon.com/Statistical-Consequences-Fat-Tails-Pr... Beware that it may be way more advanced than what you'd expect though.
The takeaways from NNT’s books are summarized in the top Amazon review. The summary is actually pretty useful and relevant and highlights some of the pitfalls of applying common statistical concepts to fat tailed distributions and the change of mindset that is needed.
We tend to gloss over assumptions like finite variance or iid but they matter a lot for reasoning correctly on fat tailed distributions.
Also the law of large numbers only works if you don’t have a game over scenario or fat tails.
https://www.amazon.com/gp/aw/review/1544508050/RMD3OUG0WQWWY