How much of pod shop alpha is tied to their model?
Talking to MM pod shops, it seems like they all are very focused on the model, trying to pick up inflection points in the business. They are all doing the same math. It just seems like this would be a place that is more or less commoditized, so wondering how much of their alpha is generated through their model work? model assumptions etc?
For us, 0. The model is table stakes and just a way to accurately do some quick maths on our views vs cons. Analysts that are hyper focused on their model aren’t necessarily producing alpha. Modelling capex spend better than the next guy for a name where volume durability is being debated isn’t going to add edge.
Having a process that gives you ~5% better odds of understanding how volumes are shifting in and across channels vs the rest of the street is alpha, especially given that will compound over time.
Detailed models are very important, but they should not be a source of edge.
What type of set-up do you work in? Traditional pod?
My pod is more model focused, but I sometimes question if that's beneficial.
Often there are so many big & compounding assumptions between revenue and EPS that the model just gives a false sense of security. Of course we do scenario analysis, but often that just tells me "you can really get any number, lol". But then the PM still asks me "So what's our EPS?". Sigh.
Other days, I spend hours re-reading the transcripts to incorporate detailed guidance and commentary, and my model is indeed highly accurate. But then the stock reaction is driven by some high level color on the call instead.
(We don't spend time on parts of the model that don't matter, though, e.g. BS/CFS for TMT companies, unless where required for valuation.)
If you are so model focused, how incremental is your model for the the screening and decision-making process? I was placed on a well-performing pod during my internship and was shocked how little the model mattered for the trades, in line with the first comment here.
I go through the model line-by-line with my PM and we look at the deltas to sell-side consensus and 3P data for basically anything that's mappable to VA / Yipit / MScience / etc.
Where available, we also compare to buy-side consensus and guidance.
Then we obviously also check what the deltas have been in previous periods, to establish a baseline.
Model alone is just one part of the decision, but I'd say it's usually very critical. Of course the model implicitly also incorporates my views on trends, competition, etc. The components of the decision framework (that I can't describe here) are not fully mutually exclusive.
Do you mind elaborating because I got confused? When you say compare to 3P and consensus, do you have your own estimates that you are comparing against? When you identify a delta, is that a potential differentiation? Thank you.
Compare own projections to 3P, consensus, buyside consensus, guidance, etc.
And yes, that's the differentiation.
We also track how our past estimates have differed from the above "comps", but tbh that's not captured systematically enough to be useful.
So we instead check how past period actuals differed from their comps back then, e.g., is consensus typically too high/too low? Does management typically guide in line with street? Etc.
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