Why do P72 Analysts leave so quick?

I've been looking at P72 employment data on LinkedIn and noticed that many analysts decide to leave after only 1-2 years working at the firm. Not sure if that's normal in the HF industry or not, but does anyone know why this is the case whether it is an industry-wide problem or specific to P72? Am I missing something or interpreting the data wrong? I'll be interning in Academy next summer so I'm wondering if I should prep for exit opps in advance like how bankers prep for PE in advance. TIA!

Because the industry revolves around money and if you’re not making money, you are of no use to the firm. Also - if you don’t fire people, people will take the firms risk limits less seriously which is not what they want. Welcome to the industry.

The academy program is almost a year and you’re not really going to leave during training even if you don’t like the people. People are leaving a lot after 1 or 2 years because they aren’t lasting long after the program. Based on the people I know there, this isn’t because they’re getting canned but because they hate it there. Might get MS for this but apparently the culture is god awful.

You will learn more next summer but % of academy graduates still at p72 is quite high. p72 has the lowest churn among the big MMs. if your pm gets fired they'll look to put you on another team. 

Have heard from people who know people (…) that it is one of the more lenient MMs but the work life balance for juniors is poo (work weekends and do stupid Sunday team calls because why not), the culture is getting shouted at and the pay is not that great vs. other MMs so any half decent Point72 analyst will probably be tempted to bail as soon as they become plug-and-play

Well that’s the format of the academy. Also could be nature of mm model….if you lose money you’re shown the door quickly

Generally, would you say that exits have been strong? I think this can be revealing as to whether they were fired or voluntarily jumped. What % of exits would you say were to a comparable or better fund? 

Asking bc I haven't done my own LinkedIn research yet but plan to next week after I buy a one month premium plan. Would be happy to share / compare findings. Did you try to systematically collect data or did you just click on a bunch of profiles that came up first?

If you're good at MM-style earnings trading, does that make you a good fundamental deep value investor? That's what I'm curious about. Skillset for the former is staying on top of a bunch of market signals and building really thorough models for the next 3-9 months, whereas skillset for the latter is developing a robust sense of competitive adv and putting countless different pieces together in your head. In theory, there doesn't seem to be much skill transferability.

But if P72 indeed has many ppl exiting to tiger cub SM style funds, then perhaps it is true. 

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Tried systematically collecting data through premium but ran into several problems. LinkedIn's search algorithm is simply bad; there is significant noise in search data and I've read quite a bit into manipulating their search algorithms for more accurate results yet that has yielded no useful results. LinkedIn is filled with people putting P72 (and for that matter, any somewhat highly-regarded firm) on their profile when in reality they've only attended some virtual insight series - LinkedIn can't tell the difference. Results are also filled with people not in fundamental investing roles but work or have worked at the firm and would therefore be irrelevant to the scope of this analysis. I could also just be terrible at searching for people so who knows.

Therefore most of my findings have been anecdotal so take this with a grain of salt, but they usually exit to places where my first reaction isn't, damn this person probably got fired and had to jump ship quick. Haven't seen employment gaps and most exit opps are respectable from what I've seen.

Not mentioned so far is that a bunch of these guys are not getting actual investing offers (getting put on data support teams)

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