To get the typical q’s out of the way:
Fund type - blue chip MM/MS
Group - macro/commodities (commodities focused, won’t be more specific for anonymity)
YOE/TC - in 3rd year, comp was ~ analyst 3 BB ish year 1, associate 3 BB ish year two. Base + 150, 300% roughly. First really big base bump this year, not a huge amt of room for base to grow generally as capped at fairly low numbers even for decades of experience. my boss is ~200k/yr, and he’s got 20+ YOE, hasn’t gotten a raise since started w Fund ~10 yrs ago. For context, I started at 6 figures base, and got 5 fig raise first year but < 15%, and just short of 50% after last year.,. So I don’t have much more room to grow, though maybe w inflation the sr bases shift higher too. Anyways, enough abt $.
Background - studied a tough STEM (not compsci) in ugrad, somewhat non traditional path (dropped out of school for a few years after a year at one school, returned and finished in 1.5 ish at different school. Neither target.). One relevant (but non HF) internship summer before graduating.
High-level role desc - this changed as built out analytical tools for my coverage, but in general balance my time between reviewing and updating my fundamental forecasts for supply and demand of the commodities I cover, writing code for models (almost entirely model with code not excel, can’t say language for anonymity/proprietary), talking to people in market, coming up with investment ideas/validation of forecasts relevant to trades (call this trade strategy and tracking), meeting with boss to review balance sheets/investment progression/new investment theses/progress of analytics construction (this is once every one to two weeks formally, but we talk every day abt market and new fundamental info that comes in etc.
WLB: hours vary. Vol in my market not so seasonal, so always “busy”, but really workload is event-driven and has evolved over time. Early, when everything was new, I was building everything out from scratch, and I was building rep within group (team is < 10 ppl) consistently worked > 60 hrs/wk. one winter worked every day for 45 days or so, probably 80-100 hrs a week but that was for project I was super excited abt. After first ~15 mos, more like 50-60 hrs/wk including work I do most Sunday afternoon/evenings - I have full ownership over my coverage, and so I will ramp up my hours when building something new. This is usually when there’s a big market opportunity in new product group that I end up picking up, or when we see something in my existing coverage that my analytics don’t sufficiently cover and can expand the depth of the existing tools and so enter targeted-push-mode.
Tried to be as comprehensive as possible here so can get to the meaty questions. Won’t be checking this constantly, but will do my best to keep up. Hope that I can be helpful in some way!
You obviously have a very non-traditional background for a MM HF, especially coming from a nontarget. What about your profile do you think stuck out to the people hiring you? Why pick you out of the thousands of applications they likely received?
You’d be surprised, I think. Most of the people I work with are not super well-pedigreed Ivy leaguers (some of them are, for sure). What all of them are is smart as hell, have a unique and very first-principles oriented process for evaluating the world, and are extremely self-reflective (at some gradient across these dimensions and some others).
I had a relevant internship, with a commodities trading shop, had a nearly perfect gpa, and during my internship built out some pretty innovative analytical/trading processes - will qualify that with: for being a total newcomer to the markets, and having 10 weeks. I didn’t like solve the market obviously, the project just demonstrated I thought about/approached problems in a way they thought would be compatible to their process.
For commodities, HFs and the likes generally hire from ABCD, supermajors or whatever other commodities firms are out there. Why did they decide to pick you over someone with exposure to the commodities youre in?
There’s a few questions along the lines of “why you”, so I’ll answer just the component of that you asked about, which is - why me compared to someone who’d covered the commodities I work on now.
There’s a fairly easy answer - hiring someone experienced is expensive as hell, and they are unlikely to adapt their way of doing things to how a new group operates (especially a trader that’s the best in the world at their coverage. Usually not a very humble bunch).
For specifically the commodities I cover, the guys who run my team wanted them to be built in a more quantitative way that top, experienced discretionary traders hadn’t done and were averse to migrating to (if it ain’t broke…)
so, they got someone that would be eager to learn the new way of doing things, and could do it for - at least initially - a substantially lower cost.
Oh, also, I had an internship at a major commodities shop.
Thanks for taking the effort. Maybe not the type of question you were expecting:
What percentage of commodities you cover (don't have to say which) do you forecast will be up from current levels - in 3m, 6m, and 12m? On inflation more broadly, if you have a view?
I like this question!
I was remarking to a coworker today actually - it seems like in the last two years, and certainly in last 12 months, we’ve made more money being long stuff than short it.
sounds obvious, and it probably is.
It’s hard to make a call like this. Over medium horizon, global energy prices (particularly gas and power) are going to cause inflated cost of production and ongoing supply chain issues to stick around. This messes with global supply and demand equilibriums, and in some cases concentrates climatological risk to global supply and thereby increases risk of global shortfalls in goods spreading.
One thing I can say, though, is that we should be seeing greater equilibrium found in where value is captured in supply chains. For a time, wholesale prices of many goods just totally disconnected from retail/consumer prices. This was because traditionally elastic buyers became inelastic because as buyers who had their pipelines drawn to zero as they had to shut down came back online (and were largely px inelastic in the process), they were either going to keep buying goods and eat the wholesale price increase in margin for a time and eventually pass cost to consumer, or they were not going to have products to themselves remain operational. Obviously not binary on/off, but that’s just the high level description. So as we’ve normalized supply pipelines (largely… obviously lots of disruptions still), and the consumer demand shock is not on the upswing still, we have been and will continue to move towards new equilibria relative pricing at different points in supply chains.
Just curious about how you applied. Did you meet someone during your internship who was looking for someone?
I applied through an online portal. I sent a bunch of hail-Mary apps to a number of major funds and just happened that the right guy looked at my resume, called me one day, and the rest is history.
How confident are you in your (and your PM's) ability to generate alpha long term without significant drawdowns? How do you personally deal with the "volatility" of an MM HF seat?
I am currently in two MM HF processes and confident that I will get an offer from at least 1 of them but I'm struggling a bit to understand how real the possibility of getting fired is at an MM and how much control I have over it.
Your question is a harder one to answer than it appears, but I'll give you the short answer then the long one.
Ultimately, unless you have some great line into the sector that the PM covers or something, you're not going to really know about them in particular and honestly, depending on your level of experience may not be a great idea to walk into a mtg with a PM and be like "show me your monthly return history" hah. Maybe just explicitly address that concern with the PM, depending on the sense you get from them. On one hand, it's a "take the opportunity and don't ask questions" type culture, but on the other hand people respect directness (if you have the chips to do so..) That said, I'll share my thought process with you.
Getting fired sucks. I was nervous I'd get fired in first year, and have signed a lease in an expensive city, and have to go back to my lower-risk, lower-reward (and more importantly - the lesser opportunity to learn, though would have been great opp still) job offer out of ugrad with my tail between my legs. Most firms fire 10-15% or so per year (from what I've heard). I will say though, I know several teams that were down for 12-18 months and had not a soul fired.
All of this stuff is hard to know, but if I was to communicate one thing here it would be - think about what your "fallback" is. It's probably the same thing you'd be doing if you chose to turn down the fund seat. So if you get to take a shot that has huge upside, and your downside is going back to where you would've otherwise been, that's a free call option (though some ego pain in process maybe..). And further, people talk about these places like they're butchers shops. Me and a buddy who's worked for my firm for a while have a mental framework of about ~33-50% turnover on 18-24 month basis. That's not firings, that's quitting too. Pretty stark, but not that bad. And two years of TC in a good seat at one of these spots can be 10-20x median household income for US (and this is for a junior employees). That's life changing. So, it depends on your pathology and what you value. I ultimately chose this job over the more secure one because I had the opportunity to learn from/work with the singularly best in the world in this field. And given that opportunity, I'll take it every time. I'd rather be the dumbest guy in a room full of some of the smartest people on the planet, than the smartest guy in a room full of mediocre (or even very smart) people, ten times out of ten.
Regarding what I do to deal with the volatility? It varies. Sometimes it's healthy, sometimes it's unhealthy. I've gone through times where I worked out a lot, woke up early and meditated, etc. I've gone through times where I partied a lot and chased women. I've gone thru times where I did too many drugs. I've gone through times where I was miserable at work and fought with my boss incessantly, and was fueled by that anger. I've gone through times where I was on cloud-9. Now, I will say, after a few years, it seems like the skew is becoming more to the negative on a social-emotional basis, but not entirely one-sided.
Crazy long rant about alpha and drawdowns and such below. read at your own risk.
Avoiding significant drawdowns and generating edge are inextricably interwoven. Long term edge only exists if I have a seat from which to execute on any edge I have today/may generate in the future.
I acknowledge here that I am being perhaps overly simplistic, but this stuff is complicated, and I could (and may one day) write a long and wildly complex examination of these markets, underlying relationships, information theory, human psychology, probability, the cruel hand of God (hah), etc. I try to give a thorough but traceable decomposition/description below.
Let's call long-term edge and avoidance of drawdowns: sustained, successful risk-management.
To discuss the sustainability of my PM's successful risk management, I think it's important to first juxtapose to what it looks like for me vs him.
For me, this is based upon things outlined above, which ultimately are relatively quantifiable outside of PnL space. I can back-test models, verify soundness of single theses as they do or don't play out fundamentally, track and attribute errors in my forecast - both qualitatively and quantitatively. I can acknowledge the limitations of the analytics we have, and quantify the strengths. Limitations are generally harder to quantify, and this is intuitive right - the bulk of a probability density curve is where most of your results occur, and your strength is exactly the stuff you capture in your process. The inputs to your model are defined positively, that is they are explicitly incorporated in a way that is tractable and can be readily communicated. The possible inputs to your model which are not in your model defined negatively, that is they are the set of all possible inputs minus the set of inputs. This is harder to understand, harder to explain, and harder to work with generally.
This is all to say, my PM doesn't have to build a product that generates money with nothing but his brain and a computer. I touched on it above, but the third step in the call it 'data-science' portion of my process is information consumption. Part of my success has been that I automated steps 1-2 extremely quickly. Meaning, relative to other market participants who have done minimal automation, or skill wise do not have the ability to automate these processes as it's not easy necessarily, or they do not have the institutional buy-in and have extremely high expectations of ramp up time - so their incentive is not to innovate, nor to spend time up front to save time down the line. Remember, edge doesn't exist without a seat to deploy risk from - if they can't ramp up in the allotted time, miss PnL targets as a result and get fired, all that innovation is 'for naught' on paper (I would absolutely argue against that, but I'm explaining why not saying it's optimal - my stance on this is revealed by the way I've structured my career to date). But, I still have to a) find the sources b) work with engineering to scrape the data - if you've ever worked with engineers you know they can be very difficult to communicate, collaborate with. This is dimension in which I believe that most institutions including my own fail, and why those who can organically communicate and collaborate across business (or, human) and technical (or, computer) functions at a high level in any field are generally wildly successful (I know plenty of wildly successful people who can't do this, but I know ZERO people who can do this and aren't wildly successful at whatever they do). Back to the point. I do all of this, and relative to I would say nearly any person who's my age/YOE am in a position with an extremely high ratio of information consumption / information. My PM has almost an undefined ratio of this, though. And, he gets my/the team's filter on top of the information consumed before he consumes it (though admittedly as you are all seeing with this post, my filter doesn't guarantee extremely low volume - hah). Now, there is still the top-level skill, which is taking that information and monetizing it. I am probably underweighting this here (and in general) - perhaps that's due to my bias as an analyst :). In my experience with this sort of spread in reality, it's somewhere in-between. He doesn't necessarily have to source edgy info from his team, he can maybe get that from consultants, reading the newspaper, watching price screens, etc, but let's be real - the days of PTJ trading the deutschmark/yen cross at 3:30 am in his upstate NY home on a NYT article he read are gone.
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