Is this broadly the right idea?

Going to be interning at an MM in a few weeks and just wanted to check up on my approach/ask about stuff I'm still a bit unclear on.

For context i study a degree completely irrelevant to finance but I've gone through the technicals and understand the mechanics of a model/dcf and can build my own integrated 3FS from scratch. However I wanted to get ideas on forecasting and identifying drivers for the assumptions. I've have my own scrappy(?) approach of thinking about businesses and analysing them and it was good enough to get a summer but i'd like a headstart on overhauling it since I feel incompetent lol.

I've done a lot of wider reading on getting deep on stocks/names at an MM both on here and through people like Rich Wallace and Brett Caughran for around a year as well as some wider reading on forecasting and have come to understand that a lot of the work involved identifying 3-4 key drivers and then layering each one by looking into what they're tied to and developing a view on that. I wanted to know how you actually approach doing that?

Firstly I've never explictly figured out what a driver is, I've just been looking at the line items I think are probably relevant for the business, like revenue/growth rate and then disaggregate to see whats really driving that growth, looking into the unit economics and then researching the biggest contributers/fastest growing (if management is focusing on one too) and then developing a view on what that's going to do. I then feed that into the model. To be honest though, a lot of the time the base/bear/bull scenarios i sensitise seem like gut feeling variations on my forecasts +/- a few percent rather than a proper rigorous analysis. How do you outline what 3 drivers really matter? How do you go about assigning and absolute numerical value to a forecast?

I do a similar thing for operating expenses that are significant and maybe pricing if i think it'll impact margins in the coming quarters but I'm a little confused as to when to care about specific line items...I know how to model schedules etc but sometimes there's no thesis to be made or its just not important so the item should be straight lined/modelled as a factor of something else but this seems non-intuitive to me. Bit of guidance here would be great too

I appreciate a lot of this is just stuff I'll have to figure out by going out there and building views and models and learning by doing but I thought it best to try learn from others' experiences before interning. I have my own approach to this based on the research I've done and my own personal way of looking at a company/trying to estimate forecasts but it seems a bit scrappy rather than a formal appreciation of having a proper process. Feel like if I can't figure this stuff out relatively quickly into my internship then I'm going to struggle...

Thank you 

 
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I'll take a stab and then those with more MMHF experience can comment. You are basically doing everything right for the most part already. Once you get to the job you will have a lot more sources of information other than the public filings from companies - namely sell side research, alt. data / research sources, interviews/transcripts with industry insiders, and meetings with management teams. 

Once you get those other inputs, you will have a lot more information to help you flush out the drivers. The chances of you finding a massive variance are low. A common thing that can happen is that management just had a bad quarter and their guidance was soft (but maybe out of conservatism thanks to uncertain macro). Stock multiple compresses and you got a revision downwards. You have developed information that shows maybe not next quarter, but the quarter after that, there should be a re-accleration to previously expected growth rates. The market likes to extrapolate out the now into the future, and maybe your model shows that in 2 quarters there will be an inflection in growth or margins thanks to a few key variables.

Maybe it was NVDA. Stock was down a ton - end market data was very mixed - memory in data center was looking awful, china was a question, capex from hyperscalers was fine-ish, but through your network of interviews and alt data you saw that despite data center capex being on the same trend, it was shifting massively towards accelerators instead of CPUs/memory. Looking at the model, you saw that CPUs were down but hyperscaler capex was fine, so maybe NVDA is actually rapidly gaining share - and any % shift in that end market had a huge impact. More importantly, the multiple and current price gave you a somewhat decent margin of safety or skewed risk reward to make that bet (sort of fabricating things here but you get the point). 

You will rarely come across a situation where you have high conviction that revenue will be 20% higher next quarter - but you will often find situations where the market is extrapolating out something too much, and you are playing for the pop at an inflection point. Building conviction in that inflection point comes from focusing on the right leading indicators that feed your key drivers in the model, and verifying it through meeting with insiders, management, and "alt data".

 
Intern in HF - EquityHedge

"I've gone through the technicals and understand the mechanics of a model/dcf and can build my own integrated 3FS from scratch.... I've have my own scrappy(?) approach of thinking about businesses and analysing them and it was good enough to get a summer..."

Could you detail how you've learnt the technicals/mechnics of a dcf, how you learnt how to build your own, & way of analyzing firms pls?

 

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