What do I need to learn to land a seat on an Equity Derivatives desk?

Title, currently lined up for a 2025 internship in NYC doing Equity S&T. Know 1 alumni who previously worked on the bank 2 years ago and did derivatives, one of my interviewers also did derivatives. Thinking about reaching out to them but want to have a solid understanding (or atleast a basic one) before I talk to them.

Besides starting to read the Natenberg book and understanding how the Black-Scholes model / what the Greeks mean and how they work, how can I become as competitive as possible? I want to come in with enough knowledge to be a better pick than the other interns to be completely honest. Have access to a Bloomberg Terminal as well.

Would be very grateful for any info.

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Did not intern in eqds but rates vol at a French bank this past summer - all the interns who got returns/good reviews knew python coming in and were mostly some type of engineering/cs/math major. I noticed that coming in with a solid quant background was more helpful that the basic understanding of vol you get from reading a textbook. Obviously having read natenberg will put you ahead the first couple of weeks but the desk will teach you what you really need to know. So I would be able to know the couple lines of python needed to pull from Bloomberg/kdb/ur banks infra, do some basic analysis (regression, pca, etc) then make a pretty chart.

 

(1) Hustle extra hard -- no one expects you to know everything, but you need to try to jump on as many learnable opportunities as you possibly can

(2) Have a great attitude / coachable mentality -- you will get yelled at, it's normal, but you're on the team

(3) Practice inputting orders into different systems (e.g. use a demo login for retail software, and practice putting in multi-legged options in 3+ systems under 20 seconds)

(4) Practice shouting and loudly confirming / communicating -- overcommunicating isn't a thing on the trading floor (unless you're the trader/risk taker :P)

 

Sorry to ask to be spoon-fed, but could you give me some examples of retail software where I could practice inputting multi-legged options so I can prep?

 

Besides learning the theory as you mentioned, make sure you have a solid background in python (specifically pandas, scikitlearn, and other data science packages)

 

Thank you, I have zero understanding of Python currently but I will look into those packages and see if I can teach myself. I have a strong background with computers.

 

1 - make sure you understand your greeks before starting (vega/delta/gamma). how many S&P 500 Jun25 ATM options do you need to get $1Mn vega exposure?

2 - if you don't know any python how are you going to do any grunt work to prove yourself? definitely learn python

3 - work harder than anyone else, at least for the internship (first in, last out!)

4 - if you have access to Bloomberg, follow news on NI OPTIONS, NI QUANT, NI GLOBALMACRO

5 - per (2), definitely learn python, and then get used to Pandas/Numpy, and given you have access to Bloomberg, pulling data from their API.  e.g. for each name in S&P500 (or some subset), what are the stocks with the most options volume? how does that compare to SPX/SPY options?  try to understand the options landscape (even if you might not be working with vanillas directly).  what's the average realized vol of S&P 500 stocks (or some subset) over the last month? how does it compare to the S&P 500 index realised vol?   How does is vol in US now relative to Europe and Asia?  

6 - don't expect to be handheld - show initiative and ownership for any work you do. don't expect anyone to 'check' your results, make sure they are right first time. if there's something you don't know, be honest, but if you present something as done, make sure it's right.

 

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