What does it take for an engineer, to be a portfolio manager at a Quant hedge fund?
I am a pre final year chemical engineering undergrad with minor in data science. I have always been fascinated by the way people at hedge funds go the extra mile and find less crowded strategies or maybe even undiscovered strategies to gain high returns. I gained interest in the field by doing Wharton's online business and risk modeling and a couple of courses on trading algorithms. I want to get into Quant hedge fund as I find it extremely fascinating being a mix of financial knowledge and data science. I am prepping for my CFA lvl 1. I want to know what is the path I should tread on to hopefully become a Quant hedge funds portfolio manager someday or maybe even have my own (I know sounds farfetched but yea worth a try, I guess!)
Dude, spare us the (fake) life story of why you want to be a hedge fund PM. It is okay to say you googled what the highest paying job is and are now super interested in being a hedge fund PM.
To answer your question, could be possible if your school has a strong name, you have great grades and can impress at interview. That said, tone down the whole PM dream, many associates and analysts never make them. Apply for grad roles and see where you get.
Input is much appreciated, let's see how things turn out
path is more or less 1) get job at a mega quant fund, do signal research there for a few years (e.g. D.E. Shaw, AQR, Two Sigma, Citadel GQS, etc.). Try to specialize / develop expertise in a strategy. 2) once you've seen enough signals and are confident you can run a book on your own, wait out your non-compete and start building your book. 3) Go to Millenium or any quant multi-manager, and take a shot at running money. If you crush it, great you will make $$ and maybe you can start your own firm once you build a name for yourself. If not, go back to step (1).
Good luck with getting to step (1) after college.
How exactly do you do step 2? The signals are probably constructed from data from expensive data vendors that you would only have access to at a firm. are you suggesting buying this data as an individual person? trying to use free data sources?
There are plenty of things to build in non-compete that only require free or cheap data (e.g. price/volume signals, signal combination, t-cost optimization, etc.). Hope the non-compete is not too long and your new employer will have data on their platform (i.e. keep this in mind when picking (1) and (3)).
For 3) what's the survival rate? How many actually end up being profitable and survive at MM?
not positive but i think quant PMs probably have a higher rate of success at MMs relative to fundamental PMs. More risk controlled/systematic so less likely to blow through risk parameters (i would assume). Probably still not great though.
Odds are a lot better than other entrepreneurial paths, lot worse than surviving in a quant analyst job. Let's say "proving yourself" and keeping your job is being 1 sharpe for 2 years:
1) If your edge just equals t-cost and you are rolling the dice, you have a ~10% chance of making it. 2) If you're actually good and are a 2 sharpe, you have a
Will firms in (1) only hire newly minted graduates that recently finished undergraduate/graduate degrees? Or will they also consider individuals who worked in quantitative roles on the sell-side (quants, strats, systematic research, etc)?
go on linkedin and check it out. my experience is that these places (especially two sigma) will interview most people who have the educational background. you just get put through the ringer with coding tests and difficult interviews. but as long as you have a STEM degree from a good school and some experience doing data science or quant work they'll probably give you a shot. getting the interview isn't usually that hard.
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