after reading the interviews on M&I, if research analysts and IB guys spend a small portion of their time building models or woring with their already built models, what career path would spend a majority of their time constructing models?
I wouldn’t say it’s a career “path” – if you’re stuck building models, which is a fairly foundational role in either banking or research, it means you’re stuck in place and aren’t moving up.
I see, thanks
agree.
What you will eventually learn hopefully is that modeling is largely a waste of time outside of transactional models. The amount of really high quality insight you can get from a model without being privy to inside information is generally (but not always) not enough to make a really informed decision, so the only thing you know for sure is that your model will be wrong. I have a personal rule that if I can’t model it in <30 minutes or sketch it out on scratch paper, the investment is too hard for me. That has consistently helped me avoid bad investments. Modeling often provides a false sense of comfort.
In my opinion, it’s most useful for reverse engineering current market values of equity, or operating value, to derive mispricing of investments based on what the market has priced in in terms of growth, return, and rejnvestment. If for example, breaking down the PE ratio of a big firm tells me that the expected growth of earnings is more than 10% for the next 5 years and 6% in terminal period, then it’s most likely overvalued. That saves potentially days of research and modeling.
There is a path. It is a path of a Quant.
I can’t think of even one example where that would have been relevant for me but to each their own. I religiously avoid dcf models and reverse engineering PE multiples.
Plenty of case studies.
IBM back in 2000-2001 had a PE ratio that promised a growth in revenue of 20% annually. That would mean growing by almost $150 billion in ten years. Rightfully so, the market corrected heavily when the stock price plummeted.
Check BABA’s IPO as well. It’s showing simillar mispricing solely based on breaking down either the fundamentals of the metrics, or the CAGR of FCFF in deriving fair value of equity.
This
IBM is your best case study from 2001? I think that proves my point, not yours. Probably I could have looked at IBM for 60 seconds and told you the PE was too high as Internet stocks were crashing. You are writing about academic stuff, people don’t do that stuff in the real world, at least not if they want to be taken seriously. I would get laughed at if I pitched that as an investment thesis.
Also, please short baba.
It was a quick case study that comes to mind without looking up actual numbers. It’s also easy to look back and assess the relative valuation of firms, than it is at it’s present time. The bubble happened for a reason, people were willing to pay money at that price level.
A low PE can also mean overvaluation, again, depending on the quality of growth and assumptions priced in.
Who said anything about pitching stocks. You can make a terrible thesis on investment, and still be a hit analyst if you perform well. You could use technical analysis behind doors and bullshit your way through a pitch, as long as you deliever results.
bromion and former trader are correct.
MrSmart, you are conflating ‘results’ with ‘process.’ Results do talk, but without a good process, employers/managers have no idea if you were actually good or if you just got lucky. And frequently, luck isn’t repeatable, nor is it sufficient to convince your PM to put money behind your ideas.
Strongly agree with this. A lot of the time a quick, back of the envelope model/valuation will be about as useful as an overly detailed one with a lot of bells and whistles.
OP, If you’re looking for a role that is heavily involved in modelling in excel then look at risk. It won’t really be valuation type modelling but you’ll spend less time there working in PowerPoint.
Unfortunately, while bromion might be right regarding uselessness of models, firms want you ot have these skills when you are interviewing.
You say you have plenty of examples but then give an obscure example from almost 15 years ago and can’t name others without looking up the data. I call BS. My guess is you are a level 2 candidate with only academic knowledge. That’s okay, just don’t become overly reliant on what you read in a book. Pro tip: if what you are talking about was a panacea, it would already be completely commoditized by quant funds. Modeling skills are good to have and help at the entry level but become less and less useful over time.
Sounds like you want to be a quant or risk management. And the world of financial models is much broader than stock valuations, although that is going to be what most people here focus on.
When I was in FP&A, I spent 75% of my day working with Excel models. But like others said, its an entry level type of spot. The guys that get paid are the ones that can do something with a model.