Seeing fellow co-workers models make me want to puke

Do you have some of those colleagues whose models are just absolutely stinky. Now imagine all of my co-workers being the following:


No KPI modeling (cRPO, billings, ACV), formatting straight out of the sell-side crap and didn’t even bother to simplify / make things visually bearable, model everything under the sun in 3-year seasonality, if things don’t plug right in the model then literally just hard code (instead of going back to company financials and fill the hole), has an outsized beat / miss in outer quarters and doesn’t even bother to fact check cuz they thinks they boss.


Model standard should be one of the highest integrity item across all funds. Guess my boss just tolerates low quality individuals. No wonder why returns stink. I’d literally puke if they dare to touch my models

 

To be clear, the job is investing rather than modeling companies for its own sake. The returns on incremental time and effort past a certain point are non-existent

Models can help you sensitize for certain variables and identify broad ranges for valuation. But you can’t make up for talent, judgment and (especially) luck with a better model. It sounds like you might think otherwise.

 

Not pushing back on this, but, at least for me, I don’t see how I derive the proper edge needed in my process if I don’t have a view on the key KPIs and game that into catalysts. What’s the point of having a model if you don’t have proper inputs / assumptions? Visual pleasantry is for self-sufficiency as much as for better peer reviews, as well. 

 

How dare a model have a beat / miss in outer quarters! If it’s not within 5c of street in Q3 2024 the model sucks

 

Thus your average boomer going into the Analyst Day thinking about EV/TAM while forgetting about the long-term billings guide being a fluke and loses 5% alpha day after Analyst Day (not that he cares about anything like this anyways)

 

My PMs basically use napkin math and our performance has been strong over time

I used to think like you and modeling is important to my personal process, but over time have come around to the idea that people with a strong understanding of business economics / return structure and good value judgment can still do well without the false precision a detailed model provides (also helps you avoid believing you’re more accurate just because you have a spreadsheet that justifies your view)

Point being that I know in HF world super granular models / KPI differentiation is often used as the explanation for your variant view but some of us in sleepy LO world are doing fine without all that. You would probably have an aneurysm looking at the excel screenshots my PMs share - on an unrelated note I’m a gridline guy now

 

Helpful feedback. It definitely feels like the more you rise in seniority / own risks in the book, the more you need to be able to sniff the stock from miles away and arrive at quick decisions on business / KPI trends even before plugging the numbers into the model. Model helps with complex scenarios but yeah beyond that not much value-add other than justifying the thesis / presenting outcomes of alternative scenarios. I personally just tend to be more bottom-up / parse the puzzles together to arrive at a conclusion at last.

The LO process in primary research / engaging business consultants is definitely light years more meaningful than chucking numbers and sniffing the cRPO for Q2 etc. (I'd prefer to talk to experts myself anyways).

I love gridlines as it helps with visual organization

 

My personal process has involved modeling it out like you say. Over the years my PMs have seen basically every business model under the sun and can pretty easily figure out what the key drivers of a business are without having to model it in a detailed way. Most of their time is spent thinking about/debating those drivers and forming a view on them. They can read the 10-k and look at Bloomberg/FactSet historical financials to understand the financials of the business - if there are specific KPIs worth monitoring they will throw them into Excel (but as I said, suuuuper rough).

I feel like understanding intuitively how a business works comes with time and reps, and as I said modeling remains important to my personal investment process (though I don't kill myself making a crazy model because then it becomes analysis paralysis). What I am still developing, and what seems to enable my PMs to make informed decisions on stocks, is that they are very good at quickly getting a handle on what expectations are embedded in market price and whether or not they feel there is asymmetry one way or another. They can pretty quickly get a feel for if an idea is worth spending time on and what they need to spend their time on if so.

 

Also would add that model content really varies depending on the name you're looking at. For instance, if this is an early-stage/novel, hyper growth surgical procedure asset with plenty of cash and still far from profitable trading on a EV/revenue multiple, I will spend most of my modeling energy on decomposing top-line drivers (simplified: patients -> retention/compliance -> consumables/patient/month -> gross-to-net -> revenue) and not very much time modeling out balance sheet items or a highly detailed expense build. Over the near-term (few quarters), the stock is going to trade on beat & raise momentum (or loss thereof), and nothing else. 

More important than the model is the work you do outside of spreadsheets to inform your model drivers.

And to the guy/gal above me - one of the best short sellers I know (he can pick 'em long too) is basically a pure napkin math guy. You can be a great financial modeler, fresh out of IB -> PE, hyper detailed and be an absolute shit stock picker. It's part of the process (and at times an important one), but it's merely a tool at the end of the day. Detailed models don't generate alpha in a vacuum. Not a jab at PE folks, I just work with a guy who comes from PE background and his models make mine look like absolute garbage (and he's a great analyst, but not because of his model formatting & detail).  

 

Agreed. Varied level of granularity depending on which part of the financial statement drives your thesis, if at all. Some sectors are more intuitive to modeling but for other sectors it really may just be bookkeeping historicals so you have it when you need it. Though I still prioritize visual pleasantry and granularity of details just so it helps me stay organized / not missing out on something that may matter down the line.

Primary research is always the primordial way to build your thesis IMO but you either need to pay personal visits to trade partners / attend conferences or pay an onerous fee to expert consulting firms (r.e. Gartner) to gain that edge, which is time-inefficient and a disadvantage if you need high idea velocity.

 

I have a slightly different view. I think that people mistake complicated models with ones that are easy to follow.

I think building out models help you understand the key drivers in a business, which can help orient you on where to spend time in DD. Given the lack of information, I think it's silly to spend time building every detail if you don't have a good reason to have a view (ie creating a crazy schedule for something that is  

What I will say however, is having easy to update models that are cleanly organized and formatted makes the process of following trends and keeping track of information much more seamless which is why I think it's worth it to invest the time upfront

On the SS models point, frankly these guys are covering so many companies that I can't imagine they actually care much beyond getting the next quarter right

 

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