Q&A: HF Analyst
Have watched this site for a long time. Taken a lot of value out of it. Hoping to give back now. I'm at a sector-specific fund. Had a pretty non-traditional route to public equities: went from MBA to banking/consulting and then to a HF. Don't want to discuss the recruiting process aside from if you try really really hard to network your probability of success increases. That non-traditional route leaves me not knowing a lot - for example, reading a few posts in the HF forum here seems to imply MMs play quarterly earnings but SMs don't because they're long-term focused. Is that true? News to me.But I have come to know a few things in my now 3rd year in this role. And I'm hoping this AMA can help
I won't discuss recruiting, compensation, or my background beyond what's above. imo thinking "i have a background just like him" and that giving you some sort of confidence that you'll get a HF job is not helpful. Comp is discussed in the 2022 comp thread. And recruiting is discussed widely enough that I don't see value add there - you make a stock pitch, you see whether you jive with the other analysts and PM, you receive an offer / you don't. Pretty simple.
Happy to discuss any other topics that may be helpful. Unlike the Tiger Cub AMA, I will check in and actually answer questions. I've posted a non-earnings season day to day summary below, which seems to be a popular topic for some.
6am:
Wake up, stretch and light workout in living room, on the desk by 7am
7am:
Read WSJ, check major movers pre-market, clear out inbox with overnight sellside and subscription newsletter emails - the purpose of these items is to get a pulse on what people are talking about while thinking the entire time: Does this change my thesis on the topic (assuming I have one) or am I going to forget this an hour from now. If I'm going to forget this an hour from now, why am I reading it.
Pre-market open:
Team meeting to discuss news for the day
~930am-4pm:
Work on a new pitch idea, get tired of reading filings so go back to reading interesting news about an existing name (eg, article on The Verge, some longer writings from sellside, survey results from GS sellside, etc.), go back to working on new pitch idea. The new pitch idea in my mind is a pretty raw process. I just read everything that's public (filings, earnings/conference transcripts, sellside) and try to discern the difference between what I know, what the market thinks, and what sellside is pushing, and see whether there's any light between those value markers.
I'm probably not going to explain it well but if the market thinks this is the greatest company ever as illustrated by its multiple and sellside has some 50% 1-yr average upside price target, you could think: well is this just a forever-high multiple business and I should just jump on? Will it normalize whether from higher rates, decelerating post-COVID fundamental drivers, etc. All of this to say: What will make the stock go up or down and what's my view on those things that could make the stock go up or down.
In addition to learning about a name (filings, news, convos w IR, etc.), the model building part really only takes 2-3 days. Maybe I'm just bad at modeling but you really only need revenue to FCF, chance in cash balance, and assume no debt paydown so hold the balance sheet constant and let the cash accumulate. Building out these working capital inputs like AR days, or having all the tranches of debt laid out like you're building some LBO for a pitch in banking may be helpful - but if it is I don't know what it's helping.
Post-market close:
Team meeting to discuss what happened today
Night:
Shifting from online to offline and back again is pretty random but largely I use the night time to get catchup on readings. Most brain energy is used up during the day so I try to avoid heavy lifting at night.
During earnings season, the above is different in that my 930-4pm window is spent updating quarterly models from filings to check whether growth for this year and next are on track with my thesis and then reading mgmt commentary to understand what they're saying, checking myself to see whether I believe what they're saying, then making some conclusion on where the company is versus 24 hours before when I didn't know this new information.
I think the key in my seat is:
What is your view. You need to have a view. Even if you lack confidence in that view, having a view I have found to be the most important part of this job. Make fun of the talking heads on Bloomberg or CNBC but at least they have a view, even if it's a copy paste from some MS report. You'll get on these calls with management and hear other investors' questions and think: "Have these guys read any of the company's filings? What are they talking about?" or "They are rephrasing sellside's thesis. This is not helpful." -
Perhaps sellside is right, and it's okay to have a view that's equivalent to sellside. But I'd recommend not reading sellside prior to looking at a new stock. It'll skew your judgment and have you rely on oft-erroneous logic/data/bias. But I haven't been at this game too long, so I may still be in middle school while others here are in college.
Hit me with some questions. Here to help.
Great user name lol.
One example: hypothetically, a company saw average revenue per customer of $10 historically and it went to $15 during Covid. What will the ARPU be post COVID? Why? You could just make bear base bull cases of $11 $14 $17. See what that implies for yoY revenue growth, look at the corresponding valuation metrics for those kinds of growers, then figure out an implied multiple to use to arrive at your target price.
Another example: some big budget IT product with a really long sales cycle sells a moderate amount in 2020 then has a monster Q1 21. Is that monster revenue from pent up 2020 demand because customers now feel comfortable spending with better line of sight to a post Covid world? Does this mean it’s a one time great quarter? Or is the monster growth sustainable and we are in a new demand regime for that end market? Spread the same bear base bull cases as above.
Sorry if too high level. Trying to avoid specific companies so as to maintain anonymity. But lmk any follow ups
I only have a few friends in public equities and we're all at long shorts. The common thread is we all seem to be "entrepreneurs" in that no one really cares what we do all day so long as we generate ideas that make $$$. There is some bit of desk/online "facetime" but if I'm on youtube and someone comes to my desk, i don't switch tabs to hide it. that was not the case in banking where facetime/perception mattered much more. so you have largely way more control over your schedule because there's no one checking your work and it's just all about the final pitch output. i'm sure PMs have different management styles but mine does not micro manage and largely leaves me off to wander and come up with ideas on my own. it's a bit daunting with how much autonomy we have but also fun because you can go look at whatever you want so long as it's in our sector vertical. but assuming i'm the outlier for a second, even if we were very output driven (you have one week, give me a pitch), I'd imagine you would still be able to go at your own pace because, again, there's not 3 layers of assoc/vp/director/md/corp dev manager at client checking your work. the lack of iterations and few people caring about xls/doc/ppt formatting leaves you significant time to just focus on reading, learning, and outputting in whatever format you want. so maybe the takeaways are: figure out check-in cadence with your boss when at a HF, and then understand if they have templated output (all pitches need to look like this) or if you're just free to form the end product as you wish. both of those variables will impact your daily time spent.
Waiting for the Pizz comment "how old are you and how much do you make and how much are you worth?"
Three Q's on modeling:
1) Hardcoding estimates using % of Sales/XYZ tends to feel somewhat unconvincing. Any tips to combat this? What is your bottom-up process for modelling the IS to FCF?
2) Are there any financial modeling resources you’ve found to be valuable? (Do you think sell-side models are good proxies to learn from?)
3) Depending on style: How do you think about modeling quarterly eps estimates and stress testing range of outcomes?
Interested in these questions. How simple is your model? You just do a back of the envelope and flex a few KPIs?
What does your PM want to see before putting on risk? A simple model with some bullets ok? Or do they want a few page memo? More DD for bigger positions?
I usually have as detailed a build as possible for revenue. For example, site by site if it's physical locations, or product by product if that's available. Sellside models are good if it's a recent IPO name I think bc IR's model usually ties to sellside. But with each quarter further into future the 'assumptions' that sellside backs into aren't factual so it's difficult to rely on.
So I'd probably have 1-2 levels of depth on the volume side, flex the price side, and then spit out a range on revenue. On the revenue to FCF build, similar to what Joel Greenblatt talks about in his books, I'll try to have my own definition of FCF and build to that. Specifically going from EBIT to FCF and ensuring all the recurring, non-one-time things are included is key and very subjective. There's also the debate of pre vs. post SBC. I tend to do post and mark in my 'red flag' column whenever a company has significant higher SBC as % of sales or G&A than industry peers.
The modeling resources I used were the usual suspects - TTS and macabacus being most helpful.
Hardcoding the SG&A % of sales to your point isn't ideal. But I think what's more important is thinking through the range for your scenarios. Could GM go from 78% to 81% in the next two years? Could SG&A go from 15% to 12%? The only real references are history, what peers at similar growth stages have done, and mgmt commentary. But I think getting the % right is less relevant than getting the range of outcomes as narrow as possible. Solve for narrowness not precision is how I've grown to think about it. But also acknowledge I'm new at this.
My team doesn't play earnings so we're less focused on decimals of eps. But I will say I'm increasingly finding quarterly modeling to be much more valuable than this current year quarterly then annual thereafter. Instead I'll do three years of quarterlies because it'll make me think about seasonality and if I'm doing revenue by product on a quarterly basis I'll see: OK, they've added $1.4M historically QoQ for this product. Can they do that again this quarter? They're ramping up sales offices in Latam. OK, let me check if it's a quantum difference in headcount - Careers website and LinkedIn Jobs board say yes they're hiring lots - OK I think maybe that $1.4M could become $1.7M given more headcount ads and continued demand from the market (TAM growth). This is definitely a new development for me as I've grown into this role but this idea of quarterly range of outputs are increasingly helpful for me at least. Hopefully that addresses your #3.
Jay - I'd say my model is quite simple. I spread comps, spread KPIs, and do the revenue to FCF as written about previously. But I'd say I spend a lot of time staring at the screen and thinking critically: Can this company actually accelerate revenue from $1.4M to $1.8M and why? Is it new customers from sales team headcount adds or more sales from existing customers because they're underpenetrated. so I'll strip out that granularity as low as possible based on the decision making of mgmt as communicated on earnings calls and conference interviews.
PM basically wants to see all of the above and why I'm sure about that $1.8M figure, assuming that's a main river of valuation. For example, if it's an EV/EBITDA business I'll focus much more on margins while if it's some tech EV/S name I'll just worry about that $1.4M to $1.8M progression and then unit economics on incremental revenue added relative to ramping of S&M spend. Alex Clayton at Meritech's IPO breakdowns aren't very deep but they're a good high-level way to view companies in this regard for unit economics. Additionally - knowing your conviction level is another variable to consider and I think what PMs try to consider. Are you excited about this pitch because you want to be right or are you excited because it's actually true that the company is under/overvalued. I think most good PMs try to sniff out that difference.
how old r u and how much do you make?
Questions 2 and 3 I’ll pass on. Only relevant I think if you’re coming to work with me. Hope that’s ok.
I know the stories, meaning I’ve read the filings, for probably 25-35 names. I actively follow 15-20 of those, so in the event one of them goes down 20% I could quickly whip up a pitch on why we should or shouldn’t buy. Of the 15-20, I keep models for probably 10 of them. Of the 10, we have active positions in 7 of them. I’d caution these breakdowns though because I don’t know at all if this is the median or an outlier relative to other funds. I only really touch the model during earnings season or if we are thinking of increasing or reducing position size. The vast majority of my time is spent in filings or reading interview transcripts - trying to learn about the company’s story and financials.
Having a view was probably the most difficult thing because it’s so easy to read news and just adopt that view. Read some GS equity strategy saying buy industrials and financials. Underweight tech and discretionary. And suddenly that’s what your view is. I think that’s just human nature. So getting away from that is important imo.
The modeling is quite straightforward if you’ve done banking analyst programs. I’ve heard shops like Melvin model quite a bit but that makes me wonder: what exactly is being modeled? Your granularity is largely limited to filings. Maybe you can go 1-2 levels deeper with some GLG call but beyond that I’ve never really understood when people say a fund is very “modeling heavy or has modeling monkeys hired from GS TMT”. That doesn’t make sense me but would enjoy any views of folks who may know the answer to that.
Other resources I’d suggest:
Yen Liow talks on YouTube
Columbia business school stock pitch competition with Ackman is quite interesting to hear the logic and questions judges ask. You can pick up patterns if you watch the past few years a few times.
Pabrai’s writings are interesting. Pretty similar to Klarman’s margin of safety concept imo but maybe others have different interpretations.
Then just reading about the long list of big famous bets. Soros on currencies. Ackman on Herbalife. Lampert on Sears real estate. Im sure theres many others im forgetting. But reading about why big trades worked and specifically delineating between how the investor saw something others didn’t and the investor just getting lucky I think helps for learning and pattern recognition.
Thanks a lot for doing this. My questions:
1) any tips on reading 10k/transcripts/filings more efficiently/quickly?
2) any tips on learning about the company's story more quickly?
3) any tips on finding/focusing on useful information more quickly? Most reports/books contain too much useless information (to make them longer)
4) how do you stay focused or avoid information overflow?
VP in ERCould you provide a more condensed book recommendation list? I ask because I feel like there are too many books to read, on top of the investor letters. And do you even care about "value investing" in the HF world? I get that you need to have a deep understanding of how to value business (valuation). But does reading "margin of safety" really add value to HF investing? Value investing definitely seems to matter depending on the style of your PM. Most I've interviewed with will skew more growth or value expertise and their book will look accordingly.Shorter book list is honestly hard to write. Nothing comes to mind and my bookshelf is crowded. I just read everything folks recommend or cite. And if it seems boring I stop because I know I won't remember what I'm reading. Stuff like Klarman is helpful for mental models imo. I think the premise of your question suggests there's some short list of content somewhere that if you read you'll be a better investor. I don't think that's the case. I think you just read high volume and then whatever naturally you remember when a situation arises is where the application of the book comes out.