Financial Modeling and 10k
Hi guys, long time lurker here. Wanted to get some of the experienced HF analysts and equity researchers opinions on this! I was reading public company resources (10k, earnings presentation) that has no information relating to the actual number of units/volumes sold by a company. How do you go about forecasting the unit economics of the business (i.e., price and volume)?
There will be a revenue segmentation/disaggregation note or table somewhere. At the very least you can do it from the business segments. Usually if you read the notes on revenue they’ll tell you how much is price vs volume (even if they don’t give you the exact units and price).
Also depends on business model, price and volume doesn’t make sense for some.
If you want you can still make assumptions for volume and price growth and forecast based on those, even if you don't know historical values. Of course it will involve guesswork and the value can be limited.
Maybe you can find some historical/current alt data for price and/or volume and try to get company numbers aligned with it.
Very few companies are going to give you such granular units x price breakdowns in their 10k filings. It really depends by industry / company how we can forecast this. With semiconductor companies, this can be more straightforward - sellside and buyside analysts typically try to triangulate units x price through various supply chain checks, for example by checking 1) NVDA's wafer suppliers - how many wafers did NVDA order / how many chips can be cut from 1 wafer, 2) NVDA's chip testers - how many chips did they test this month, 3) NVDA's rack assemblers - how many racks did they assemble this month etc.
If it is a software / internet company - then units x price becomes a bit more "ambiguous". There are 3rd party research providers who can check on company's largest customers - e.g. how are ads budgets / users growth tracking at the company. This can provide a "directional" view on the growth rates (accelerating or decelerating) for the quarter - but they tend to have more room for error, especially if a software company has a long tail of small/mid business customers.
You just have to learn to be creative to find ways or alt data to triangulate the information you need. And then after that, you also have to figure out whether this alt data is already priced into the stock at current levels...
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